File size: 108,329 Bytes
6fa4bc9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441 1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455 1456 1457 1458 1459 1460 1461 1462 1463 1464 1465 1466 1467 1468 1469 1470 1471 1472 1473 1474 1475 1476 1477 1478 1479 1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696 1697 1698 1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 | {
"paper_id": "2020",
"header": {
"generated_with": "S2ORC 1.0.0",
"date_generated": "2023-01-19T13:05:07.660740Z"
},
"title": "Terminology in Written Medical Reports: A Proposal of Text Enrichment to Favour its Comprehension by the Patient",
"authors": [
{
"first": "Rosa",
"middle": [],
"last": "Estop\u00e0",
"suffix": "",
"affiliation": {},
"email": "rosa.estopa@upf.edu"
},
{
"first": "Alejandra",
"middle": [],
"last": "L\u00f3pez-Fuentes",
"suffix": "",
"affiliation": {},
"email": "alejandra.lopez@upf.edu"
},
{
"first": "Jorge",
"middle": [
"M"
],
"last": "Porras-Garz\u00f3n",
"suffix": "",
"affiliation": {},
"email": ""
}
],
"year": "",
"venue": null,
"identifiers": {},
"abstract": "The empowerment of the population and the democratisation of information regarding healthcare have revealed that there is a communication gap between health professionals and patients. The latter are constantly receiving more and more written information about their healthcare visits and treatments, but that does not mean they understand it. In this paper we focus on the patient's lack of comprehension of medical reports. After linguistically characterising the medical report, we present the results of a survey that showed that patients have serious comprehension difficulties concerning the medical reports they receive, specifically problems regarding the medical terminology used in these texts, specifically in Spanish and Catalan. To favour the understanding of medical reports, we propose an automatic text enrichment strategy that generates linguistically and cognitively enriched medical reports which are more comprehensible to the patient, and which focus on the parts of the medical report that most interest the patient: the diagnosis and treatment sections.",
"pdf_parse": {
"paper_id": "2020",
"_pdf_hash": "",
"abstract": [
{
"text": "The empowerment of the population and the democratisation of information regarding healthcare have revealed that there is a communication gap between health professionals and patients. The latter are constantly receiving more and more written information about their healthcare visits and treatments, but that does not mean they understand it. In this paper we focus on the patient's lack of comprehension of medical reports. After linguistically characterising the medical report, we present the results of a survey that showed that patients have serious comprehension difficulties concerning the medical reports they receive, specifically problems regarding the medical terminology used in these texts, specifically in Spanish and Catalan. To favour the understanding of medical reports, we propose an automatic text enrichment strategy that generates linguistically and cognitively enriched medical reports which are more comprehensible to the patient, and which focus on the parts of the medical report that most interest the patient: the diagnosis and treatment sections.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Abstract",
"sec_num": null
}
],
"body_text": [
{
"text": "When we talk about written communication between doctor-patient, we refer to all the written information handed over during a person's healthcare practice and which is included in his or her clinical history. Within all this written information, the medical report constitutes a key element for the patient, since it contains the diagnosis and the prescribed treatment (Del\u00e0s, 2005; Falc\u00f3n and Basagoti, 2012) . A medical report is a written document issued by a medical professional regarding a specific healthcare procedure undergone by a patient -for example, a visit to the accident and emergency department or a hospital admission. Starting from a linguistic analysis of a corpus of 50 medical reports of patients affected by a rare disease in Spanish and Catalan (CORPUS-ER) 1 , we have established a set of linguistic parameters which characterise this type of texts and which might interfere, if not used properly, the reader's full comprehension of the medical report. These parameters, of different linguistic nature, have been grouped in different categories: (a) pragmatic-semantic; (b) syntactic; (c) lexical 2 ; and (d) orthotypographical. Each one of these major categories has been broken down into several specific parameters. For example, within the lexicon parameter, we have considered the use of acronyms, terms with Greco-Latin formants and symbols, among others. Moreover, lexically speaking, medical reports have a high number of terms, an excessive use of non-expanded acronyms, abbreviations and symbols, and a high occurrence of semantically non-transparent terms.",
"cite_spans": [
{
"start": 369,
"end": 382,
"text": "(Del\u00e0s, 2005;",
"ref_id": "BIBREF12"
},
{
"start": 383,
"end": 409,
"text": "Falc\u00f3n and Basagoti, 2012)",
"ref_id": null
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Introduction",
"sec_num": "1."
},
{
"text": "Terminological units or terms are lexical units of a given language which in a determined communicative context activate a very precise specialised property (Cabr\u00e9, 1999) . Words with specialised content in the medical context (e.g. traditionally referred to as medical terms) activate a 1 The complete analysis can be found in R. Estop\u00e0 (Coord.) (2020), Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n precise, concise and appropriate specialised sense that enables us to talk about health and illness related topics in a proper way. Some of these terms are well known, for example the ones we experience first-hand (e.g. lung, eye, flu, menstruation, muscle) ; others, although not strange and apparently semantically transparent, are not easy to define without previous biomedical knowledge since the can be more abstract or polysemous (e.g. gene, symptom, treatment, cholesterol, cancer, stem cell) ; while many others are extremely opaque for a non-expert from the point of view of their meaning (e.g. acromegaly, Lowe's syndrome, CT scan, PET scan, ALS, perimetrosalpingitis, lobectomy) . Traditionally, terms used in medical texts in Spanish and Catalan are mostly formed by lexical bases from ancient Greek and Latin (Bonavalot, 1978; L\u00f3pez Pi\u00f1ero and Terrada Ferrandis, 1990; Bernabeu-Mestre et al., 1995; Guti\u00e9rrez Rodilla, 1998; Wulff, 2004; Anderson, 2016) ; but at present, medical terminology is also influenced by languages such as German or French, but mainly by English. Thus, words like, buffer, bypass, core, distress, doping, feed-flush, flapping tremor, follow-up, handicap, lamping, mapping, odds ratio, output, patch test, pool, relax, scanner, score, or screening (Navarro, 2001; Garc\u00eda Palacios, 2004) are just a small sample of the large number of terms that come directly from English into Spanish. At the same time there is the belief that the medical terminology is precise, concise, objective and even neutral, as recommended by Terminology ISO standards and many manuals and studies on medical terminology (Bello, 2016; Navarro, 2016; Del\u00e0s, 2005) . However, from different perspectives it has been found that such a belief cannot be true, as language is significantly complex and communicative situations in medicine are very diverse. It must be remembered that medical terminology is not only used by medical professionals, but also by the entire population -primarily patients and their families-in order to express opinions, fears, concerns and doubts related to their health and illness.",
"cite_spans": [
{
"start": 157,
"end": 170,
"text": "(Cabr\u00e9, 1999)",
"ref_id": "BIBREF10"
},
{
"start": 288,
"end": 289,
"text": "1",
"ref_id": null
},
{
"start": 646,
"end": 689,
"text": "(e.g. lung, eye, flu, menstruation, muscle)",
"ref_id": null
},
{
"start": 868,
"end": 931,
"text": "(e.g. gene, symptom, treatment, cholesterol, cancer, stem cell)",
"ref_id": null
},
{
"start": 1065,
"end": 1121,
"text": "CT scan, PET scan, ALS, perimetrosalpingitis, lobectomy)",
"ref_id": null
},
{
"start": 1254,
"end": 1271,
"text": "(Bonavalot, 1978;",
"ref_id": "BIBREF7"
},
{
"start": 1272,
"end": 1313,
"text": "L\u00f3pez Pi\u00f1ero and Terrada Ferrandis, 1990;",
"ref_id": "BIBREF26"
},
{
"start": 1314,
"end": 1343,
"text": "Bernabeu-Mestre et al., 1995;",
"ref_id": "BIBREF6"
},
{
"start": 1344,
"end": 1368,
"text": "Guti\u00e9rrez Rodilla, 1998;",
"ref_id": "BIBREF21"
},
{
"start": 1369,
"end": 1381,
"text": "Wulff, 2004;",
"ref_id": "BIBREF44"
},
{
"start": 1382,
"end": 1397,
"text": "Anderson, 2016)",
"ref_id": "BIBREF2"
},
{
"start": 1508,
"end": 1716,
"text": "English. Thus, words like, buffer, bypass, core, distress, doping, feed-flush, flapping tremor, follow-up, handicap, lamping, mapping, odds ratio, output, patch test, pool, relax, scanner, score, or screening",
"ref_id": null
},
{
"start": 1717,
"end": 1732,
"text": "(Navarro, 2001;",
"ref_id": "BIBREF32"
},
{
"start": 1733,
"end": 1755,
"text": "Garc\u00eda Palacios, 2004)",
"ref_id": "BIBREF19"
},
{
"start": 2066,
"end": 2079,
"text": "(Bello, 2016;",
"ref_id": "BIBREF5"
},
{
"start": 2080,
"end": 2094,
"text": "Navarro, 2016;",
"ref_id": "BIBREF33"
},
{
"start": 2095,
"end": 2107,
"text": "Del\u00e0s, 2005)",
"ref_id": "BIBREF12"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "What is a Medical Term?",
"sec_num": "2."
},
{
"text": "In linguistics, terminological units are lexical units which belong to the lexicon of a language. And the lexicon of any language is exponentially complex and almost never complies with the attributes that are presupposed for the scientific lexicon: neutrality, objectivity, monosemy (Navarro, 2016) . It is true, however, that there are some terms that we could label as univocal, descriptive and neutral, such as poliomyelitis, which has a \"unique\" meaning, since it represents a concept in its totality and corresponds to an object \"constructed\" from reality in a specific conceptual structure (that of medicine). But it is evident that on many occasions medical terms are polysemous (for example, the acronym AA is used to refer to acute abdomen, but also to amino acid, abdominal appendicitis, ascending aorta and abdominal aorta); and they also might variate, in other words, have synonyms (for example, a stroke is also known as a brain attack, a cerebrovascular accident, a cerebrovascular insult, a cerebral vascular accident, a haemorrhagic stroke, an ischemic stroke, etc.; and it is also referred to with acronyms such as: CVA or CVI). This diversity of designations and diversity of senses, in the case of polysemy, results in confusion amongst specialists and in uncertainty amongst patients. For which uncertainty intermingles with the emotional burden that comes with dealing with a disease (Garc\u00eda Palacios, 2004) . Ultimately, as Wermuth and Verplaetse (2018, pp. 87) summarize: \"Although classical terms still represent the foundation of medical terminology, also words from general language, abbreviations and acronyms, eponyms, slang and jargon words, synonyms, metaphors and metonyms, and made-up words are substantial parts of today's medical language\". And, as part of medical language, medical reports also include all these types of units.",
"cite_spans": [
{
"start": 284,
"end": 299,
"text": "(Navarro, 2016)",
"ref_id": "BIBREF33"
},
{
"start": 1407,
"end": 1430,
"text": "(Garc\u00eda Palacios, 2004)",
"ref_id": "BIBREF19"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "What is a Medical Term?",
"sec_num": "2."
},
{
"text": "Medical reports record the diagnosis, or the therapeutic procedures carried out during any healthcare visit. This type of text has very particular linguistic characteristics which, taken as a whole, make it difficult to be fully understood. Currently, medical reports are mainly expository documents (Estop\u00e0 and Dom\u00e8nech-Bagaria, 2018) . This means that nominalisation in them is very high and, therefore, there are not so many verbs; consequently, the presence of terminology 3 is very high. Some surveys conducted on patients (Estop\u00e0 and Dom\u00e8nech-Bagaria, 2018 ) and on doctors (Navarro, 2016) show that terminology is one of the main obstacles to fully understand a medical report. Moreover, according to the results of the analysis carried out by Estop\u00e0 and Montan\u00e9 (2020) , terminology comprehension obstacles of a medical report can be summarised in the next four parameters: 1. Specialised knowledge accumulation: the number of terms contained in medical reports is very high in relation to the average number of words the text has. 2. Semantic opacity: terms are often not known by patients, so they are not semantically transparent. 3. Semantic confusion: medical terms can lead to misunderstandings as regards their meaning, especially if they correspond to terms of general use that have acquired a specific, specialised sense in medicine and which is, perhaps, different to their general sense. 4. Semantic ambiguity: terms variate and are subject to polysemy, which may cause them to be interpreted in different ways, which increase doubt and uncertainty. According to these authors, these four parameters can be correlated with nine indicators that allow to determine the comprehension difficulty for a patient of a medical report: A. Total number of terms in a medical report. ",
"cite_spans": [
{
"start": 300,
"end": 335,
"text": "(Estop\u00e0 and Dom\u00e8nech-Bagaria, 2018)",
"ref_id": "BIBREF14"
},
{
"start": 528,
"end": 562,
"text": "(Estop\u00e0 and Dom\u00e8nech-Bagaria, 2018",
"ref_id": "BIBREF14"
},
{
"start": 580,
"end": 595,
"text": "(Navarro, 2016)",
"ref_id": "BIBREF33"
},
{
"start": 751,
"end": 776,
"text": "Estop\u00e0 and Montan\u00e9 (2020)",
"ref_id": "BIBREF15"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Use of Terms in Medical Reports",
"sec_num": "3."
},
{
"text": "In order to demonstrate that terminology detected and analysed in medical reports lead to comprehension problems for the patients, we implemented two different strategies that complemented each other: a general automatic readability test and a comprehension survey.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Do Patients Understand Terminology in Medical Reports?",
"sec_num": "4."
},
{
"text": "Automatic readability tests or readability formulas are tools that indicate if a text is easily readable or not according to quantitative data (e.g. number and length of words, number and length of sentences). There exist different formulas of this nature developed mainly for English texts, formulas such as the Reading Ease Score (Flesch, 1948) , the SMOG test (McLaughlin, 1969) , the Flesch-Kincaid test (Smith and Kinkaid, 1970) or the Gunning FOG test (Gunning, 1952) ; but some have also been developed for Spanish: the Fern\u00e1ndez-Huerta index (Fern\u00e1ndez Huerta, 1959) , the Szgriszt index (Szigriszt-Pazos, 1993) (Table 1) , as well as with the remaining tests 4 , results showed that medical reports are in general difficult to read, hence the need to go further and check qualitatively some of the texts was evident in order to know if they were as difficult to read as the automatic tests reported.",
"cite_spans": [
{
"start": 332,
"end": 346,
"text": "(Flesch, 1948)",
"ref_id": "BIBREF18"
},
{
"start": 363,
"end": 381,
"text": "(McLaughlin, 1969)",
"ref_id": "BIBREF30"
},
{
"start": 408,
"end": 433,
"text": "(Smith and Kinkaid, 1970)",
"ref_id": "BIBREF40"
},
{
"start": 458,
"end": 473,
"text": "(Gunning, 1952)",
"ref_id": "BIBREF20"
},
{
"start": 561,
"end": 574,
"text": "Huerta, 1959)",
"ref_id": "BIBREF17"
},
{
"start": 596,
"end": 619,
"text": "(Szigriszt-Pazos, 1993)",
"ref_id": "BIBREF41"
}
],
"ref_spans": [
{
"start": 620,
"end": 629,
"text": "(Table 1)",
"ref_id": "TABREF0"
}
],
"eq_spans": [],
"section": "Automatic readability tests",
"sec_num": "4.1"
},
{
"text": "Further qualitative comparison showed that preliminary results of the automatic tests were neither reliable nor discriminating, because these tools are not designed to deal with highly specialised texts (high number of medical terms) such as medical reports. Therefore, it was likely that the actual readability level was even more difficult than what the automatic analysis showed.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Automatic readability tests",
"sec_num": "4.1"
},
{
"text": "The second strategy implemented to confirm the results of the tests and to demonstrate there is a real comprehension problem for the users of medical reports, consisted in a survey which was conducted to a set of people (all of them have been patients and some of them currently are or will in the future be patients).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Comprehension survey",
"sec_num": "4.2"
},
{
"text": "How was the survey done? The next steps were followed to carry out the comprehension survey: 1. Selection of one of the medical reports from the CORPUS-ER after the qualitative analysis considering the mean of terminological density and extension. 2. Drafting of a linguistically and cognitively enriched version of said report. 3. Preparation of two comprehension surveys, one for each version of the report (original and enriched), with identical structure and similar questions. 4. An in-person implementation of both surveys was carried out with a group of 100 people. The group was divided into two subgroups: in the first stage, survey A was conducted to group 1 and survey B to group 2; and in the second stage, A to 2 and B to 1 (in this way we avoided the problem of participants learning or getting used to the content of the report from one survey to the other). 5. Statistical treatment of the results (paired-sample t-test in the case of lexical-related numerical variables). 6. Analysis of the results. So, once the linguistic and terminological parameters that cause comprehension problems had been detected and analysed, we selected a real medical report from our corpus and then produced a new version of it in which said problems were addressed, in order to ensure the maximum understanding by the patient. Although some of the changes made during the enrichment process are in line with the recommendations of the so-called plain language, or simplified language (NARA guide, 2012), we chose to call the new version of the report a linguistically and cognitively enriched version, since no information was removed from it and no terms were discarded nor information paragraphs were altered. The steps taken to enrich the report were the following: 1. correction of grammatical errors (e.g., punctuation marks, missing verbs, order of the elements of a sentence) and typographical inadequacies (e.g., font); 2. including descriptions and paraphrases of ambiguous or highly specialised lexical elements (terms, phraseology); 3. construction of simple phrases that match with Catalan and Spanish prototypical sentence structure of SVO (subject, verb, object); 4. controlling and expanding abbreviations (abbreviations, acronyms, symbols); and 5. personalising the text to bring it closer to the patient (explicit subject, personal verbal form). In this way, we avoided lowering the cognitive load of these texts, while writing specialised information (term related) in a more explicit way, enriching the report, since the main premise was that patients are not usually able to infer from the text the information naturally inferred by health professionals (e.g. not knowing unexpanded abbreviations or semantically opaque terms). Therefore, a medical report enriched from different perspectives (expanding abbreviations, paraphrasing terms, formulating sentences with conjugated verbs and explicit subjects...) allows the healthcare provider to ensure that the text is explicit, prevents the patient from making erroneous inferences, favours an adequate interpretation of the information and a correct understanding of the full text. Based on these considerations, from both versions of the medical report (the original and the enriched one), two comprehension surveys with an identical structure were prepared which included the following sections:",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "4.2.1",
"sec_num": null
},
{
"text": "\u2022 General data for control (sex, age, level of education, mother tongue and profession). to know explicitly which of the two was better understood and which of the two was preferred by the patient considering that the information was the same. Once the general survey parameters were applied, it was essential to carry out a pilot measurement survey (Scheaffer et al., 1987; Sampieri et al., 2000) on a small sample of 25 participants to test its functionality. Testing the survey allowed us to verify the parameters and modify them when needed. After the pilot, the survey was conducted to a total of 100 participants of different ages and level of studies. Participants were divided into two groups of 50 and all of them responded both surveys. On a first stage, the original report survey was conducted on one group and the enriched report survey on the other group; on a final stage the opposite was done: each group took the corresponding remaining survey. This allowed us to ensure there was no learning between one survey and the other.",
"cite_spans": [
{
"start": 350,
"end": 374,
"text": "(Scheaffer et al., 1987;",
"ref_id": "BIBREF37"
},
{
"start": 375,
"end": 397,
"text": "Sampieri et al., 2000)",
"ref_id": "BIBREF36"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "4.2.1",
"sec_num": null
},
{
"text": "Discussion of the results The results obtained after both surveys were highly significant and discriminating. For example, in the case of the lexical-related numerical variables a paired-sample ttest was performed in order to establish the significance value for the difference between means (the mean of comprehension results of the first survey and the mean of the second one), and the p-value was < 0.0001. So, this allowed us to conclude that most of the participants: a) had difficulties in understanding the original version of the medical report -even participants with a higher educational degree-; b) did not have as many difficulties in understanding the enriched version of the medical report-even the participants with a lower educational degree-; and c) understood the enriched version of the report better than the original version.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "4.2.2",
"sec_num": null
},
{
"text": "The results shown in Chart 1 correspond to the questions intended to measure the patient's perception of comprehension of terms and acronyms within the text. Here participants had to choose what they believed made more difficult to understand the report they just read. We can observe that in general patients perceived the original medical report as more semantically opaque. For example, regarding the unexpanded acronyms, for the original report almost all the participants (92%) selected as a comprehension obstacle the fact that acronyms were not easy to understand, while in the adapted text only 27% of participants felt the same way. Almost the same happens with the perception of unknown terms and, in a lower degree, the perception of barely known terms. we scored each answer from 0 to 3 (3 = answers correctly; 2 = answers imprecisely; 1 = doesn't answer or doesn't know; 0 = answers incorrectly [because it is more dangerous for a patient's health to act incorrectly than not to act at all due to not knowing something]). Since there were 4 questions measured, the highest possible result for any participant was 12, and the lowest, 0. So, results in Chart 2 are evidence of the difference of means (which we already said they were highly significant [ < 0.0001]) in text comprehension between the original and the enriched version. While after reading the original texts, patients failed the test (4.5 out of 12), after reading the enriched version of the same text, they successfully approved the test (10.4 out of 12).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Chart 1: Perception of comprehension of the term related information in the medical reports",
"sec_num": null
},
{
"text": "So far, we have seen that the lack of understanding in medical reports is largely -although not entirely-due to the high concentration of opaque terms and acronyms. Section 4.2.2 demonstrates that actions, like including descriptions or paraphrases of highly specialised lexical elements and expanding abbreviations, can substantially improve the text understanding. However, manually carrying out this lexical enrichment is a time-consuming and labour-intensive task, hence, there is a need to automate linguistic tasks.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Can we Automatically Enrich Medical Reports?",
"sec_num": "5."
},
{
"text": "In computer science, the process of modifying natural language to reduce its complexity towards improving readability and comprehension is called text simplification (TS) (Shardlow, 2014), and it may involve modifications to the syntax, the lexicon or both. Starting in the nineties with the first TS application: a grammar checker for Boeing's commercial aircraft manuals (Hoard et al., 1992) there has been much work in TS mainly for the English language. However, since the early 2000s TS started to emerge across different languages and various categories of readers. For example, tools in Japanese (Inui et al., 2003) and Bulgarian (Lozanova et al., 2013) for hearing-impaired people, in French (Max, 2006) and Spanish (Bott and Saggion, 2011) for people with aphasia, in Brazilian Portuguese (Alu\u00edsio et al. 2008) for low literacy people, and finally in Italian (Barlacchi and Tonelli, 2013) and French (Brouwers et al., 2014) for schoolchildren or second language learners. Regardless of the language and purpose of simplification tools, there are different methods within the TS field. Systems can use them individually or in combination since they are not mutually exclusive. The most common approaches are lexical, syntactic and explanation generation.",
"cite_spans": [
{
"start": 373,
"end": 393,
"text": "(Hoard et al., 1992)",
"ref_id": "BIBREF22"
},
{
"start": 603,
"end": 622,
"text": "(Inui et al., 2003)",
"ref_id": "BIBREF23"
},
{
"start": 637,
"end": 660,
"text": "(Lozanova et al., 2013)",
"ref_id": "BIBREF27"
},
{
"start": 700,
"end": 711,
"text": "(Max, 2006)",
"ref_id": "BIBREF28"
},
{
"start": 724,
"end": 748,
"text": "(Bott and Saggion, 2011)",
"ref_id": "BIBREF8"
},
{
"start": 798,
"end": 819,
"text": "(Alu\u00edsio et al. 2008)",
"ref_id": "BIBREF1"
},
{
"start": 868,
"end": 897,
"text": "(Barlacchi and Tonelli, 2013)",
"ref_id": "BIBREF3"
},
{
"start": 909,
"end": 932,
"text": "(Brouwers et al., 2014)",
"ref_id": "BIBREF9"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Can we Automatically Enrich Medical Reports?",
"sec_num": "5."
},
{
"text": "\u2022 Lexical approach. Lexical simplification is the task of identifying and replacing complex words with simpler substitutes (Shardlow, 2014). This approach does not attend grammar issues, it only focuses on vocabulary aspects. It also comprises the expanding of abbreviations. \u2022 Syntactic approach. Syntactic simplification is the process of reducing the grammatical complexity of a text, while retaining its information content and meaning (Siddharthan, 2006) . as journals articles (Abrahamsson et al., 2014) , medical records (Kandula et al., 2010; Zeng-Treitler et al., 2007) , information pamphlets (Leroy et al., 2012) and patient information leaflets (Delaere et al., 2009; Segura-Bedmar and Mart\u00ednez, 2017) .",
"cite_spans": [
{
"start": 440,
"end": 459,
"text": "(Siddharthan, 2006)",
"ref_id": "BIBREF39"
},
{
"start": 483,
"end": 509,
"text": "(Abrahamsson et al., 2014)",
"ref_id": "BIBREF0"
},
{
"start": 528,
"end": 550,
"text": "(Kandula et al., 2010;",
"ref_id": "BIBREF24"
},
{
"start": 551,
"end": 578,
"text": "Zeng-Treitler et al., 2007)",
"ref_id": "BIBREF45"
},
{
"start": 603,
"end": 623,
"text": "(Leroy et al., 2012)",
"ref_id": "BIBREF25"
},
{
"start": 657,
"end": 679,
"text": "(Delaere et al., 2009;",
"ref_id": "BIBREF11"
},
{
"start": 680,
"end": 713,
"text": "Segura-Bedmar and Mart\u00ednez, 2017)",
"ref_id": "BIBREF38"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "Can we Automatically Enrich Medical Reports?",
"sec_num": "5."
},
{
"text": "As part of an ongoing doctoral project, we are building an online software so that it will be available from anywhere using a web browser and it will allow to deal with medical reports written in Spanish about rare diseases. It focuses on the sections with the highest concentration of terms: diagnosis and treatment. The strategies to deal with the terminological issues are a) synonym enrichment and b) explanation insertion. To the best of our knowledge, there is no similar tool in Spanish devoted to improving the comprehension of medical reports. Although there are systems for simplifying drug package leaflets (Segura-Bedmar and Mart\u00ednez, 2017) and to help hearing-impaired people (Bott and Saggion, 2011) .",
"cite_spans": [
{
"start": 689,
"end": 713,
"text": "(Bott and Saggion, 2011)",
"ref_id": "BIBREF8"
}
],
"ref_spans": [],
"eq_spans": [],
"section": "A prototype for automatic text enrichment",
"sec_num": "5.1"
},
{
"text": "This first task is meant to enrich highly specialised lexical elements by selecting their less specialised versions and adding them within the text. It also includes the identification of abbreviations and their expansion into their full form. For most abbreviations (e.g. AVC) their full form will be added (e.g. AVC -accidente vascular cerebral), but the patient-friendly abbreviations such as ADN will not have their full form (\u00e1cido desoxirribonucleico) displayed. Patient-friendly abbreviations are manually annotated as preferred term within our database. Our main datasource for abbreviations and their corresponding full forms is the Diccionario de siglas m\u00e9dicas (Dictionary of medical abbreviations) from the Sociedad Espa\u00f1ola de Documentaci\u00f3n M\u00e9dica (SEDOM [Spanish Society of Medical Documentation]). Disambiguation of polysemous abbreviations is not yet solved in this first version of the prototype thus, all the associated full forms will be shown. Regarding the highly specialised lexical elements, we chose the Spanish version of SNOMED CT to map them with a less specialised term. SNOMED CT is a multilingual structured clinical vocabulary collection of medical terms providing codes, synonyms and definitions (SNOMED, 2017). Our tool searches within SNOMED for synonyms of a highly specialised lexical element and retrieve the patient-friendly term. For example, if the term hepatomegalia is found in a medical report, then the tool searches for it in the database and grabs its SNOMED identifier (80515008 in this case). This identifier serves as a link to other synonyms and therefore, allows to select the best candidate, based on predefined parameters. In the example, h\u00edgado grande would be the associated element to pick and would be displayed as hepatomegalia (h\u00edgado grande).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Synonym enrichment",
"sec_num": "5.1.1"
},
{
"text": "Explanation insertion There are cases where no suitable terms to display are found, then it is necessary to include a short explanation for such terms. For example, the SNOMED identifier 48638002 has associated only one term, nefrocalcinosis. The added explanation to the medical report would be nefrocalcinosis (trastorno en el cual hay demasiado calcio depositado en los ri\u00f1ones). We are currently gathering, analysing and processing explanations for this kind of terms. Since a good comprehension is directly related to the quality of the information provided, we have chosen not to perform automatic explanation generation but to manually review trusted sites (e.g. Spanish version of MedlinePlus website) and adapt the information found. The main parameters we have defined to consider an explanation as valid are the following: information should always come from trusted sources, must be short, dictionary-like, homogenous and with an appropriate level of specialisation.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "5.1.2",
"sec_num": null
},
{
"text": "Dealing with any disease represents an emotional burden to patients and this burden increases significantly when they do not understand the medical reports they receive after a healthcare visit. These medical reports have a specific linguistic structure which, from the lexicon point of view, is characterised by an excessive use of medical terms and acronyms which mean for the patient: additional cognitive load, semantic opacity, semantic confusion and semantic ambiguity. Said comprehension barriers can be breached by cognitively and linguistically enriching the medical report, as has been seen in the results of the surveys. Hence, the ICT and computational techniques to automate text enrichment can be beneficial to doctor-patient communication. Our prototype aims to be used, on one hand, as a support for the healthcare professionals to generate a more patient-friendly document and, on the other, as a query tool for the patients to have a better understanding of what they are reading. Nevertheless, it is important to note that language is complex, and software may lead to mistakes so computational tools should be used only as an aid. Further work on our proposal might explore different branches like working with syntactic issues, including abbreviation disambiguation to enhance lexical enrichment, or widening the scope of application to other medical reports besides rare diseases.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusion",
"sec_num": "6."
},
{
"text": "This research paper has been written as part of the research project TOGETHER: overcoming socio-educational barriers and promoting literacy on the interferences and difficulties in understanding information and documentation aimed at families of children affected by rare diseases. RecerCaixa 2015. Avancem amb la ci\u00e8ncia. ACUP I Obra Social \"La Caixa\". The proposal of a prototype for automatic text enrichment is developed within the doctoral thesis of Alejandra L\u00f3pez-Fuentes: Automatic adaptation of biomedical terms for non-experts: the case of medical reports supervised by Rosa Estop\u00e0 and Julio Collado-Vides. This work was also supported by the project TERMMED: Analysis of lexical change and terminological variation for the creation of linguistic resources in the medical field. ",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Acknowledgements",
"sec_num": "7."
},
{
"text": "In this paper we will focus only in the lexical analysis since we are interested in showing the results regarding the terminology used in medical reports.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "Terms are prototypically nouns (e.g., dermatographia, dermatitis, dermatology, dermatologist, dermatomycosis, dermatome), since noun is the category that, by definition, binds knowledge together in a referential manner.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "For all the details and results of these tests you can check the works of Porras-Garz\u00f3n and Estop\u00e0 (2019 and 2020).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "These are real examples of terms used in the analysed medical reports.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
}
],
"back_matter": [],
"bib_entries": {
"BIBREF0": {
"ref_id": "b0",
"title": "Medical text simplification using synonym replacement: Adapting assessment of word difficulty to a compounding language",
"authors": [
{
"first": "E",
"middle": [],
"last": "Abrahamsson",
"suffix": ""
},
{
"first": "T",
"middle": [],
"last": "Forni",
"suffix": ""
},
{
"first": "M",
"middle": [],
"last": "Skeppstedt",
"suffix": ""
},
{
"first": "M",
"middle": [],
"last": "Kvist",
"suffix": ""
}
],
"year": 2014,
"venue": "Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations",
"volume": "",
"issue": "",
"pages": "57--65",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Abrahamsson, E., Forni, T., Skeppstedt, M., and Kvist, M. (2014). Medical text simplification using synonym replacement: Adapting assessment of word difficulty to a compounding language. In Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations. Association for Computational Linguistics, pp. 57-65.",
"links": null
},
"BIBREF1": {
"ref_id": "b1",
"title": "Towards Brazilian Portuguese automatic text simplification systems",
"authors": [
{
"first": "S",
"middle": [
"M"
],
"last": "Alu\u00edsio",
"suffix": ""
},
{
"first": "L",
"middle": [],
"last": "Specia",
"suffix": ""
},
{
"first": "T",
"middle": [
"A S"
],
"last": "Pardo",
"suffix": ""
},
{
"first": "E",
"middle": [
"G"
],
"last": "Maziero",
"suffix": ""
},
{
"first": "R",
"middle": [
"P M"
],
"last": "Fortes",
"suffix": ""
}
],
"year": 2008,
"venue": "Proceedings of the 8th ACM Symposium on Document Engineering",
"volume": "",
"issue": "",
"pages": "240--248",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Alu\u00edsio, S. M., Specia, L., Pardo, T. A. S., Maziero, E. G., and Fortes, R. P. M. (2008). Towards Brazilian Portuguese automatic text simplification systems. In Proceedings of the 8th ACM Symposium on Document Engineering. New York: ACM Digital Library, pp. 240- 248.",
"links": null
},
"BIBREF2": {
"ref_id": "b2",
"title": "Medical Terminology: The Best and Most Effective Way to Memorize, Pronounce and Understand Medical Terms",
"authors": [
{
"first": "D",
"middle": [],
"last": "Anderson",
"suffix": ""
}
],
"year": 2016,
"venue": "D. A. Medical Handbooks",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Anderson, D. (2016). Medical Terminology: The Best and Most Effective Way to Memorize, Pronounce and Understand Medical Terms. D. A. Medical Handbooks.",
"links": null
},
"BIBREF3": {
"ref_id": "b3",
"title": "ERNESTA: A sentence simplification tool for children's stories in Italian",
"authors": [
{
"first": "G",
"middle": [],
"last": "Barlacchi",
"suffix": ""
},
{
"first": "S",
"middle": [],
"last": "Tonelli",
"suffix": ""
}
],
"year": 2013,
"venue": "Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing",
"volume": "2",
"issue": "",
"pages": "476--487",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Barlacchi, G., and Tonelli, S. (2013). ERNESTA: A sentence simplification tool for children's stories in Italian. In A. Gelbukh (Ed.), Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing. Vol. 2, pp. 476-487.",
"links": null
},
"BIBREF4": {
"ref_id": "b4",
"title": "Validaci\u00f3n de la Escala INFLESZ para evaluar la legibilidad de los textos dirigidos a pacientes",
"authors": [
{
"first": "I",
"middle": [
"M"
],
"last": "Barrio Cantalejo",
"suffix": ""
},
{
"first": "P",
"middle": [],
"last": "Sim\u00f3n Lorda",
"suffix": ""
},
{
"first": "M",
"middle": [],
"last": "Melguizo",
"suffix": ""
},
{
"first": "I",
"middle": [],
"last": "Escalona",
"suffix": ""
},
{
"first": "M",
"middle": [
"I"
],
"last": "Mariju\u00e1n",
"suffix": ""
},
{
"first": "P",
"middle": [],
"last": "Hernando",
"suffix": ""
}
],
"year": 2008,
"venue": "Anales del Sistema Sanitario de Navarra",
"volume": "31",
"issue": "2",
"pages": "135--152",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Barrio Cantalejo, I. M., Sim\u00f3n Lorda, P., Melguizo, M., Escalona, I., Mariju\u00e1n, M. I., y Hernando, P. (2008). Validaci\u00f3n de la Escala INFLESZ para evaluar la legibilidad de los textos dirigidos a pacientes. Anales del Sistema Sanitario de Navarra, 31(2):135-152.",
"links": null
},
"BIBREF5": {
"ref_id": "b5",
"title": "Aprendiendo a redactar mejor tus informes",
"authors": [
{
"first": "P",
"middle": [],
"last": "Bello",
"suffix": ""
}
],
"year": 2016,
"venue": "Curso de Actualizaci\u00f3n de Pediatr\u00eda. Madrid: L\u00faa Ediciones 3.0",
"volume": "",
"issue": "",
"pages": "391--400",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Bello, P. (2016). Aprendiendo a redactar mejor tus informes. In AEPap (Ed.), Curso de Actualizaci\u00f3n de Pediatr\u00eda. Madrid: L\u00faa Ediciones 3.0, pp. 391-400.",
"links": null
},
"BIBREF6": {
"ref_id": "b6",
"title": "El llenguatge de les ci\u00e8ncies de la salut",
"authors": [
{
"first": "J",
"middle": [],
"last": "Bernabeu-Mestre",
"suffix": ""
},
{
"first": "J",
"middle": [
"M"
],
"last": "Perujo Melgar",
"suffix": ""
},
{
"first": "J",
"middle": [
"V"
],
"last": "Saport",
"suffix": ""
},
{
"first": "P",
"middle": [],
"last": "Alberola",
"suffix": ""
},
{
"first": "J",
"middle": [],
"last": "Borja I Sanz",
"suffix": ""
},
{
"first": "C",
"middle": [],
"last": "Cort\u00e9s Orts",
"suffix": ""
},
{
"first": "C",
"middle": [],
"last": "Mart\u00ednez",
"suffix": ""
}
],
"year": 1995,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Bernabeu-Mestre, J., Perujo Melgar, J. M., Forcadell Saport, J. V., Alberola, P., Borja i Sanz, J., Cort\u00e9s Orts, C., and Mart\u00ednez, C. (1995). El llenguatge de les ci\u00e8ncies de la salut. Generalitat de Val\u00e8ncia, Conselleria de Sanitat i Consum, Valencia.",
"links": null
},
"BIBREF7": {
"ref_id": "b7",
"title": "Le vocabulaire m\u00e9dical de base. \u00c9tude par l'\u00e9tymologie. Soci\u00e9t\u00e9s d'\u00c9tudes Techniques et Fiduciaires",
"authors": [
{
"first": "M",
"middle": [],
"last": "Bonavalot",
"suffix": ""
}
],
"year": 1978,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Bonavalot, M. (Dir.). (1978). Le vocabulaire m\u00e9dical de base. \u00c9tude par l'\u00e9tymologie. Soci\u00e9t\u00e9s d'\u00c9tudes Techniques et Fiduciaires, Paris.",
"links": null
},
"BIBREF8": {
"ref_id": "b8",
"title": "Spanish text simplification: An exploratory study",
"authors": [
{
"first": "S",
"middle": [],
"last": "Bott",
"suffix": ""
},
{
"first": "H",
"middle": [],
"last": "Saggion",
"suffix": ""
}
],
"year": 2011,
"venue": "Procesamiento de Lenguaje Natural",
"volume": "47",
"issue": "",
"pages": "87--95",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Bott, S., and Saggion, H. (2011). Spanish text simplification: An exploratory study. Procesamiento de Lenguaje Natural, 47:87-95.",
"links": null
},
"BIBREF9": {
"ref_id": "b9",
"title": "Syntactic Sentence Simplification for French",
"authors": [
{
"first": "L",
"middle": [],
"last": "Brouwers",
"suffix": ""
},
{
"first": "D",
"middle": [],
"last": "Bernhard",
"suffix": ""
},
{
"first": "A.-L",
"middle": [],
"last": "Ligozat",
"suffix": ""
},
{
"first": "T",
"middle": [],
"last": "Fran\u00e7ois",
"suffix": ""
}
],
"year": 2014,
"venue": "Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations",
"volume": "",
"issue": "",
"pages": "47--56",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Brouwers, L., Bernhard, D., Ligozat, A.-L., and Fran\u00e7ois, T. (2014). Syntactic Sentence Simplification for French. In Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations. Association for Computational Linguistics, pp. 47-56.",
"links": null
},
"BIBREF10": {
"ref_id": "b10",
"title": "La terminolog\u00eda. Representaci\u00f3n y comunicaci\u00f3n. Una teor\u00eda de base comunicativa y otros art\u00edculos",
"authors": [
{
"first": "M",
"middle": [
"T"
],
"last": "Cabr\u00e9",
"suffix": ""
}
],
"year": 1999,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Cabr\u00e9, M. T. (1999). La terminolog\u00eda. Representaci\u00f3n y comunicaci\u00f3n. Una teor\u00eda de base comunicativa y otros art\u00edculos. Institut Universitari de Ling\u00fc\u00edstica Aplicada, Barcelona.",
"links": null
},
"BIBREF11": {
"ref_id": "b11",
"title": "ABOP, automatic optimization of patient information leaflets",
"authors": [
{
"first": "I",
"middle": [],
"last": "Delaere",
"suffix": ""
},
{
"first": "V",
"middle": [],
"last": "Hoste",
"suffix": ""
},
{
"first": "C",
"middle": [],
"last": "Peersman",
"suffix": ""
},
{
"first": "L",
"middle": [],
"last": "Van Vaerenbergh",
"suffix": ""
},
{
"first": "P",
"middle": [],
"last": "Velaerts",
"suffix": ""
}
],
"year": 2009,
"venue": "International symposium on Data and Sense Mining, Machine Translation and Controlled Languages (ISMTCL)",
"volume": "",
"issue": "",
"pages": "74--81",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Delaere, I., Hoste, V., Peersman, C., Van Vaerenbergh, L., & Velaerts, P. (2009). ABOP, automatic optimization of patient information leaflets. In International symposium on Data and Sense Mining, Machine Translation and Controlled Languages (ISMTCL). Universit\u00e9 de Franche-Comt\u00e9, pp. 74-81.",
"links": null
},
"BIBREF12": {
"ref_id": "b12",
"title": "Quaderns de la bona praxis. Informes cl\u00ednics, eines de comunicaci\u00f3. Col\u2022legi Oficial de Metges de Barcelona",
"authors": [
{
"first": "J",
"middle": [],
"last": "Del\u00e0s",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Coord",
"suffix": ""
}
],
"year": 2005,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Del\u00e0s, J. (Coord.). (2005). Quaderns de la bona praxis. Informes cl\u00ednics, eines de comunicaci\u00f3. Col\u2022legi Oficial de Metges de Barcelona, Barcelona.",
"links": null
},
"BIBREF13": {
"ref_id": "b13",
"title": "Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n",
"authors": [
{
"first": "R",
"middle": [],
"last": "Estop\u00e0",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Coord",
"suffix": ""
}
],
"year": 2020,
"venue": "Delhospital Ediciones",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Estop\u00e0, R. (Coord.) (2020). Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n. Delhospital Ediciones, Buenos Aires, Argentina.",
"links": null
},
"BIBREF14": {
"ref_id": "b14",
"title": "Diagn\u00f3stico del nivel de comprensi\u00f3n de informes m\u00e9dicos dirigidos a pacientes y familias afectados por una enfermedad rara. Communication presented in the 36\u00ba Congreso Internacional de AESLA: \u00abLing\u00fc\u00edstica aplicada y transferencia del conocimiento: empleabilidad, internacionalizaci\u00f3n y retos sociales",
"authors": [
{
"first": "R",
"middle": [],
"last": "Estop\u00e0",
"suffix": ""
},
{
"first": "O",
"middle": [],
"last": "Dom\u00e8nech-Bagaria",
"suffix": ""
}
],
"year": 2018,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Estop\u00e0, R., and Dom\u00e8nech-Bagaria, O. (2018). Diagn\u00f3stico del nivel de comprensi\u00f3n de informes m\u00e9dicos dirigidos a pacientes y familias afectados por una enfermedad rara. Communication presented in the 36\u00ba Congreso Internacional de AESLA: \u00abLing\u00fc\u00edstica aplicada y transferencia del conocimiento: empleabilidad, internacionalizaci\u00f3n y retos sociales\u00bb. April 2018, C\u00e1diz.",
"links": null
},
"BIBREF15": {
"ref_id": "b15",
"title": "La terminolog\u00eda: principal obst\u00e1culo para la comprensi\u00f3n de los informes m\u00e9dicos",
"authors": [
{
"first": "R",
"middle": [],
"last": "Estop\u00e0",
"suffix": ""
},
{
"first": "A",
"middle": [],
"last": "Montan\u00e9",
"suffix": ""
}
],
"year": 2020,
"venue": "Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n. Buenos Aires: Delhospital Ediciones",
"volume": "",
"issue": "",
"pages": "59--78",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Estop\u00e0, R. and Montan\u00e9, A. (2020). La terminolog\u00eda: principal obst\u00e1culo para la comprensi\u00f3n de los informes m\u00e9dicos. In R. Estop\u00e0 (Coord.), Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n. Buenos Aires: Delhospital Ediciones, pp. 59-78.",
"links": null
},
"BIBREF16": {
"ref_id": "b16",
"title": "Alfabetizaci\u00f3n en salud: de la informaci\u00f3n a la acci\u00f3n Valencia: Itaca/TBS",
"authors": [
{
"first": "M",
"middle": [],
"last": "Falc\u00f3n",
"suffix": ""
},
{
"first": "I",
"middle": [],
"last": "Basagoiti",
"suffix": ""
}
],
"year": 2012,
"venue": "",
"volume": "",
"issue": "",
"pages": "65--96",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Falc\u00f3n, M., and Basagoiti, I. (2012). El paciente y la Alfabetizaci\u00f3n en Salud. In I. Basagoiti (Coord.), Alfabetizaci\u00f3n en salud: de la informaci\u00f3n a la acci\u00f3n Valencia: Itaca/TBS, pp. 65-96.",
"links": null
},
"BIBREF17": {
"ref_id": "b17",
"title": "Medidas sencillas de lecturabilidad",
"authors": [
{
"first": "Fern\u00e1ndez",
"middle": [],
"last": "Huerta",
"suffix": ""
},
{
"first": "J",
"middle": [],
"last": "",
"suffix": ""
}
],
"year": 1959,
"venue": "Consigna",
"volume": "214",
"issue": "",
"pages": "29--32",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Fern\u00e1ndez Huerta, J. (1959). Medidas sencillas de lecturabilidad. Consigna, 214:29-32.",
"links": null
},
"BIBREF18": {
"ref_id": "b18",
"title": "A new readability yardstick",
"authors": [
{
"first": "R",
"middle": [],
"last": "Flesch",
"suffix": ""
}
],
"year": 1948,
"venue": "Journal of Applied Psychology",
"volume": "32",
"issue": "3",
"pages": "221--233",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Flesch, R. (1948). A new readability yardstick. Journal of Applied Psychology, 32(3):221-233.",
"links": null
},
"BIBREF19": {
"ref_id": "b19",
"title": "El lenguaje m\u00e9dico, algo m\u00e1s que informaci\u00f3n",
"authors": [
{
"first": "J",
"middle": [],
"last": "Garc\u00eda Palacios",
"suffix": ""
}
],
"year": 2004,
"venue": "Panace@",
"volume": "5",
"issue": "16",
"pages": "135--140",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Garc\u00eda Palacios, J. (2004). El lenguaje m\u00e9dico, algo m\u00e1s que informaci\u00f3n. Panace@, 5(16):135-140.",
"links": null
},
"BIBREF20": {
"ref_id": "b20",
"title": "The Technique of Clear Writing",
"authors": [
{
"first": "R",
"middle": [],
"last": "Gunning",
"suffix": ""
}
],
"year": 1952,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Gunning, R. (1952). The Technique of Clear Writing. McGraw-Hill Book Co., New York.",
"links": null
},
"BIBREF21": {
"ref_id": "b21",
"title": "An\u00e1lisis e historia del lenguaje cient\u00edfico. Pen\u00ednsula",
"authors": [
{
"first": "B",
"middle": [],
"last": "Guti\u00e9rrez Rodilla",
"suffix": ""
}
],
"year": 1998,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Guti\u00e9rrez Rodilla, B. (1998). La ciencia empieza en la palabra. An\u00e1lisis e historia del lenguaje cient\u00edfico. Pen\u00ednsula, Barcelona.",
"links": null
},
"BIBREF22": {
"ref_id": "b22",
"title": "An Automated Grammar and Style Checker for Writers of Simplified English",
"authors": [
{
"first": "J",
"middle": [
"E"
],
"last": "Hoard",
"suffix": ""
},
{
"first": "R",
"middle": [],
"last": "Wojcik",
"suffix": ""
},
{
"first": "K",
"middle": [],
"last": "Holzhauser",
"suffix": ""
}
],
"year": 1992,
"venue": "Computers and Writing",
"volume": "",
"issue": "",
"pages": "278--296",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Hoard, J. E., Wojcik, R., and Holzhauser, K. (1992). An Automated Grammar and Style Checker for Writers of Simplified English. In Computers and Writing. Springer Netherlands, pp. 278-296.",
"links": null
},
"BIBREF23": {
"ref_id": "b23",
"title": "Text simplification for reading assistance",
"authors": [
{
"first": "K",
"middle": [],
"last": "Inui",
"suffix": ""
},
{
"first": "A",
"middle": [],
"last": "Fujita",
"suffix": ""
},
{
"first": "T",
"middle": [],
"last": "Takahashi",
"suffix": ""
},
{
"first": "R",
"middle": [],
"last": "Iida",
"suffix": ""
},
{
"first": "T",
"middle": [],
"last": "Iwakura",
"suffix": ""
}
],
"year": 2003,
"venue": "Proceedings of the second international workshop on Paraphrasing",
"volume": "",
"issue": "",
"pages": "9--16",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Inui, K., Fujita, A., Takahashi, T., Iida, R., and Iwakura, T. (2003). Text simplification for reading assistance. In Proceedings of the second international workshop on Paraphrasing. Morristown, NJ, USA: Association for Computational Linguistics, pp. 9-16.",
"links": null
},
"BIBREF24": {
"ref_id": "b24",
"title": "A semantic and syntactic text simplification tool for health content",
"authors": [
{
"first": "S",
"middle": [],
"last": "Kandula",
"suffix": ""
},
{
"first": "D",
"middle": [],
"last": "Curtis",
"suffix": ""
},
{
"first": "Q",
"middle": [],
"last": "Zeng-Treitler",
"suffix": ""
}
],
"year": 2010,
"venue": "Proceedings of the AMIA Annual Symposium",
"volume": "",
"issue": "",
"pages": "366--370",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Kandula, S., Curtis, D., and Zeng-Treitler, Q. (2010). A semantic and syntactic text simplification tool for health content. In Proceedings of the AMIA Annual Symposium. American Medical Informatics Association, pp. 366-370.",
"links": null
},
"BIBREF25": {
"ref_id": "b25",
"title": "Improving perceived and actual text difficulty for health information consumers using semiautomated methods",
"authors": [
{
"first": "G",
"middle": [],
"last": "Leroy",
"suffix": ""
},
{
"first": "J",
"middle": [
"E"
],
"last": "Endicott",
"suffix": ""
},
{
"first": "O",
"middle": [],
"last": "Mouradi",
"suffix": ""
},
{
"first": "D",
"middle": [],
"last": "Kauchak",
"suffix": ""
},
{
"first": "M",
"middle": [
"L"
],
"last": "Just",
"suffix": ""
}
],
"year": 2012,
"venue": "Proceedings of the AMIA Annual Symposium",
"volume": "",
"issue": "",
"pages": "522--531",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Leroy, G., Endicott, J. E., Mouradi, O., Kauchak, D., and Just, M. L. (2012). Improving perceived and actual text difficulty for health information consumers using semi- automated methods. In Proceedings of the AMIA Annual Symposium. American Medical Informatics Association, pp. 522-531.",
"links": null
},
"BIBREF26": {
"ref_id": "b26",
"title": "Introducci\u00f3n a la terminolog\u00eda m\u00e9dica",
"authors": [
{
"first": "J",
"middle": [
"M"
],
"last": "L\u00f3pez Pi\u00f1ero",
"suffix": ""
},
{
"first": "Terrada",
"middle": [],
"last": "Ferrandis",
"suffix": ""
},
{
"first": "M",
"middle": [
"L"
],
"last": "",
"suffix": ""
}
],
"year": 1990,
"venue": "Manuales Salvat",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "L\u00f3pez Pi\u00f1ero, J. M., and Terrada Ferrandis, M. L. (1990). Introducci\u00f3n a la terminolog\u00eda m\u00e9dica. Manuales Salvat, Barcelona.",
"links": null
},
"BIBREF27": {
"ref_id": "b27",
"title": "Text Modification for Bulgarian Sign Language Users",
"authors": [
{
"first": "S",
"middle": [],
"last": "Lozanova",
"suffix": ""
},
{
"first": "I",
"middle": [],
"last": "Stoyanova",
"suffix": ""
},
{
"first": "S",
"middle": [],
"last": "Leseva",
"suffix": ""
},
{
"first": "S",
"middle": [],
"last": "Koeva",
"suffix": ""
},
{
"first": "B",
"middle": [],
"last": "Savtchev",
"suffix": ""
}
],
"year": 2013,
"venue": "Proceedings of the Second Workshop on Predicting and Improving Text Readability for Target Reader Populations",
"volume": "",
"issue": "",
"pages": "39--48",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Lozanova, S., Stoyanova, I., and Leseva, S., and Koeva, S., and Savtchev, B. (2013). Text Modification for Bulgarian Sign Language Users. In Proceedings of the Second Workshop on Predicting and Improving Text Readability for Target Reader Populations. pp. 39-48.",
"links": null
},
"BIBREF28": {
"ref_id": "b28",
"title": "Writing for language-impaired readers",
"authors": [
{
"first": "A",
"middle": [],
"last": "Max",
"suffix": ""
}
],
"year": 2006,
"venue": "CICLing'06: Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing",
"volume": "3878",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Max, A. (2006). Writing for language-impaired readers. In A. Gelbukh (Ed.), CICLing'06: Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing (Vol. 3878 LNCS).",
"links": null
},
"BIBREF30": {
"ref_id": "b30",
"title": "SMOG Grading-a New Readability Formula",
"authors": [
{
"first": "G",
"middle": [
"H"
],
"last": "Mclaughlin",
"suffix": ""
}
],
"year": 1969,
"venue": "Journal of Reading",
"volume": "12",
"issue": "8",
"pages": "639--646",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "McLaughlin, G. H. (1969). SMOG Grading-a New Readability Formula. Journal of Reading, 12(8):639- 646.",
"links": null
},
"BIBREF31": {
"ref_id": "b31",
"title": "National Archives and Records Administration",
"authors": [
{
"first": "",
"middle": [],
"last": "Nara Style Guide",
"suffix": ""
}
],
"year": 2012,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "NARA Style Guide. (2012). National Archives and Records Administration. Retrieved from https://www.archives.gov/files/open/plain-writing/style- guide.pdf",
"links": null
},
"BIBREF32": {
"ref_id": "b32",
"title": "El ingl\u00e9s, idioma internacional de la medicina. Causas y consecuencias de un fen\u00f3meno actual",
"authors": [
{
"first": "F",
"middle": [],
"last": "Navarro",
"suffix": ""
}
],
"year": 2001,
"venue": "Panace@",
"volume": "2",
"issue": "3",
"pages": "35--51",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Navarro, F. (2001). El ingl\u00e9s, idioma internacional de la medicina. Causas y consecuencias de un fen\u00f3meno actual. Panace@, 2(3):35-51.",
"links": null
},
"BIBREF33": {
"ref_id": "b33",
"title": "La precisi\u00f3n del lenguaje en la redacci\u00f3n m\u00e9dica. Cuadernos de la Fundaci\u00f3n del Dr",
"authors": [
{
"first": "F",
"middle": [],
"last": "Navarro",
"suffix": ""
}
],
"year": 2016,
"venue": "Antonio Esteve",
"volume": "17",
"issue": "",
"pages": "89--104",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Navarro, F. (2016). La precisi\u00f3n del lenguaje en la redacci\u00f3n m\u00e9dica. Cuadernos de la Fundaci\u00f3n del Dr. Antonio Esteve. 17:89-104.",
"links": null
},
"BIBREF34": {
"ref_id": "b34",
"title": "Recursos para hacer an\u00e1lisis de comprensi\u00f3n a textos m\u00e9dicos escritos: an\u00e1lisis cuantitativo de tres casos m\u00e9dicos",
"authors": [
{
"first": "J",
"middle": [
"M"
],
"last": "Porras-Garz\u00f3n",
"suffix": ""
},
{
"first": "R",
"middle": [],
"last": "Estop\u00e0",
"suffix": ""
}
],
"year": 2019,
"venue": "Proceedings of the XIII Jornada Realiter",
"volume": "",
"issue": "",
"pages": "107--114",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Porras-Garz\u00f3n, J. M. and Estop\u00e0, R. (2019). Recursos para hacer an\u00e1lisis de comprensi\u00f3n a textos m\u00e9dicos escritos: an\u00e1lisis cuantitativo de tres casos m\u00e9dicos. In TERMCAT (Ed.), Proceedings of the XIII Jornada Realiter. Terminolog\u00eda per a la normalitzaci\u00f3 i terminolog\u00eda per a la internacionalitzaci\u00f3. Barcelona: Realiter and Universitat Polit\u00e8cnica de Catalunya, pp. 107-114.",
"links": null
},
"BIBREF35": {
"ref_id": "b35",
"title": "Metodolog\u00eda para el an\u00e1lisis ling\u00fc\u00edstico de informes m\u00e9dicos",
"authors": [
{
"first": "J",
"middle": [
"M"
],
"last": "Porras-Garz\u00f3n",
"suffix": ""
},
{
"first": "R",
"middle": [],
"last": "Estop\u00e0",
"suffix": ""
}
],
"year": 2020,
"venue": "Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n. Buenos Aires: Delhospital Ediciones",
"volume": "",
"issue": "",
"pages": "59--78",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Porras-Garz\u00f3n, J. M. and Estop\u00e0, R. (2020). Metodolog\u00eda para el an\u00e1lisis ling\u00fc\u00edstico de informes m\u00e9dicos. In R. Estop\u00e0 (Coord.), Los informes m\u00e9dicos: estrategias ling\u00fc\u00edsticas para favorecer su comprensi\u00f3n. Buenos Aires: Delhospital Ediciones, pp. 59-78.",
"links": null
},
"BIBREF36": {
"ref_id": "b36",
"title": "Metodolog\u00eda de la Investigaci\u00f3n. Second Edition. Mc. Graw Hill",
"authors": [
{
"first": "R",
"middle": [
"H"
],
"last": "Sampieri",
"suffix": ""
},
{
"first": "F",
"middle": [
"C"
],
"last": "Collado",
"suffix": ""
},
{
"first": "P",
"middle": [
"B"
],
"last": "Lucio",
"suffix": ""
}
],
"year": 2000,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Sampieri R. H., Collado F. C. and Lucio P. B. (2000) Metodolog\u00eda de la Investigaci\u00f3n. Second Edition. Mc. Graw Hill, Buenos Aires.",
"links": null
},
"BIBREF37": {
"ref_id": "b37",
"title": "Elementos de Muestreo. Grupo Editorial Iberoam\u00e9rica",
"authors": [
{
"first": "R",
"middle": [
"L"
],
"last": "Scheaffer",
"suffix": ""
},
{
"first": "W",
"middle": [],
"last": "Mendenhall",
"suffix": ""
},
{
"first": "R",
"middle": [
"L"
],
"last": "Ott",
"suffix": ""
}
],
"year": 1987,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Scheaffer, R. L., W. Mendenhall and Ott, R. L. (1987). Elementos de Muestreo. Grupo Editorial Iberoam\u00e9rica, M\u00e9xico.",
"links": null
},
"BIBREF38": {
"ref_id": "b38",
"title": "Simplifying drug package leaflets written in Spanish by using word embedding",
"authors": [
{
"first": "I",
"middle": [],
"last": "Segura-Bedmar",
"suffix": ""
},
{
"first": "P",
"middle": [],
"last": "Mart\u00ednez",
"suffix": ""
}
],
"year": 2014,
"venue": "International Journal of Advanced Computer Science and Applications",
"volume": "8",
"issue": "1",
"pages": "58--70",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Segura-Bedmar, I., and Mart\u00ednez, P. (2017). Simplifying drug package leaflets written in Spanish by using word embedding. Journal of biomedical semantics, 8(1), 45. Shardlow, M. (2014). A Survey of Automated Text Simplification. International Journal of Advanced Computer Science and Applications, 4(1):58-70.",
"links": null
},
"BIBREF39": {
"ref_id": "b39",
"title": "Syntactic simplification and text cohesion",
"authors": [
{
"first": "A",
"middle": [],
"last": "Siddharthan",
"suffix": ""
}
],
"year": 2006,
"venue": "Research on Language and Computation",
"volume": "4",
"issue": "1",
"pages": "77--109",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Siddharthan, A. (2006). Syntactic simplification and text cohesion. Research on Language and Computation, 4(1):77-109.",
"links": null
},
"BIBREF40": {
"ref_id": "b40",
"title": "Derivation and Validation of the Automated Readability Index for Use with Technical Materials",
"authors": [
{
"first": "E",
"middle": [
"A"
],
"last": "Smith",
"suffix": ""
},
{
"first": "J",
"middle": [
"P"
],
"last": "Kinkaid",
"suffix": ""
}
],
"year": 1970,
"venue": "The Journal of the Human Factors and Ergonomics Society",
"volume": "12",
"issue": "5",
"pages": "457--464",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Smith, E. A., and Kinkaid, J. P. (1970). Derivation and Validation of the Automated Readability Index for Use with Technical Materials. The Journal of the Human Factors and Ergonomics Society, 12(5):457-464.",
"links": null
},
"BIBREF41": {
"ref_id": "b41",
"title": "Sistemas predictivos de legibilidad del mensaje escrito: f\u00f3rmula de perspicuidad (PhD dissertation)",
"authors": [
{
"first": "F",
"middle": [],
"last": "Szigriszt-Pazos",
"suffix": ""
}
],
"year": 1993,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Szigriszt-Pazos, F. (1993). Sistemas predictivos de legibilidad del mensaje escrito: f\u00f3rmula de perspicuidad (PhD dissertation). Universidad Complutense de Madrid, Madrid.",
"links": null
},
"BIBREF42": {
"ref_id": "b42",
"title": "International Health Terminology Standards Development Organisation",
"authors": [
{
"first": "",
"middle": [],
"last": "Snomed Ct Starter Guide",
"suffix": ""
}
],
"year": 2017,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "SNOMED CT Starter Guide. (2017). International Health Terminology Standards Development Organisation.",
"links": null
},
"BIBREF43": {
"ref_id": "b43",
"title": "Medical terminology in the Western world",
"authors": [
{
"first": "C",
"middle": [],
"last": "Wermuth",
"suffix": ""
},
{
"first": "H",
"middle": [],
"last": "Verplaetse",
"suffix": ""
}
],
"year": 2018,
"venue": "Handbook of Terminology: Terminology in the Arab World",
"volume": "",
"issue": "",
"pages": "84--108",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Wermuth, C., and Verplaetse, H. (2018). Medical terminology in the Western world. In A. Alsulaiman and A. Allaithy (Eds.), Handbook of Terminology: Terminology in the Arab World. Amsterdam: John Benjamin Publishing Company, pp. 84-108.",
"links": null
},
"BIBREF44": {
"ref_id": "b44",
"title": "The Language of Medicine",
"authors": [
{
"first": "H",
"middle": [
"R"
],
"last": "Wulff",
"suffix": ""
}
],
"year": 2004,
"venue": "Journal of the Royal Society of Medicine",
"volume": "97",
"issue": "",
"pages": "187--188",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Wulff, H. R. (2004). The Language of Medicine. Journal of the Royal Society of Medicine, 97: 187-188.",
"links": null
},
"BIBREF45": {
"ref_id": "b45",
"title": "Making texts in electronic health records comprehensible to consumers: a prototype translator",
"authors": [
{
"first": "Q",
"middle": [],
"last": "Zeng-Treitler",
"suffix": ""
},
{
"first": "S",
"middle": [],
"last": "Goryachev",
"suffix": ""
},
{
"first": "H",
"middle": [],
"last": "Kim",
"suffix": ""
},
{
"first": "A",
"middle": [],
"last": "Keselman",
"suffix": ""
},
{
"first": "D",
"middle": [],
"last": "Rosendale",
"suffix": ""
}
],
"year": 2007,
"venue": "Proceedings of the AMIA Annual Symposium",
"volume": "",
"issue": "",
"pages": "846--850",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Zeng-Treitler, Q., Goryachev, S., Kim, H., Keselman, A., and Rosendale, D. (2007). Making texts in electronic health records comprehensible to consumers: a prototype translator. In Proceedings of the AMIA Annual Symposium. American Medical Informatics Association, pp. 846-850.",
"links": null
}
},
"ref_entries": {
"FIGREF0": {
"text": "B. The percentage of terms relative to all the words in the text. C. The percentage of abbreviations. D. The percentage of terms formed by Greek or Latin lexical bases. E. The percentage of terms of more general use (terms that were included in the general Spanish and Catalan language dictionaries). F. The percentage of eponyms (terms derived from proper names, usually from scientists' last names, e.g. Alzheimer's disease). G. The percentage of loanwords. H. The percentage of defined or paraphrased terms (terms where a paraphrase is used in order to explain them). I. Number of cases of formal terminological variation.",
"uris": null,
"num": null,
"type_str": "figure"
},
"FIGREF1": {
"text": "Answering questions related to previous general perceptions about the comprehension of medical reports.\u2022 Reading the corresponding medical report for the survey (original or enriched version).\u2022 Answering different questions intended to measure the perception about the understanding of the read medical report (original and enriched version). Questions such as If you didn't understand one section of the text, what do you think is the cause? a) Unknown words, b) Known words that I don't fully understand, c) Unknown acronyms and symbols, d) Unfamiliar expressions, e) Other causes, if so, which? \u2022 Answering questions intended to measure the actual understanding of the read medical report (term related questions included). \u2022 Comparing fragments of the two versions of the report",
"uris": null,
"num": null,
"type_str": "figure"
},
"FIGREF2": {
"text": "Explanation generation. Often called semantic simplification, is the process of taking difficult concepts in a text and augment them with extra information. It usually consists of generating an automatic explanation by hierarchically and/or semantically related terms. Within the medical domain automatic text simplification tools have been developed for different type of texts such",
"uris": null,
"num": null,
"type_str": "figure"
},
"FIGREF3": {
"text": "Research group IULATERM (Lexicon and Technology, ref. 2017SGR1530). (FFI2017-88100-P, Ministry of Economy and Competitiveness [MINECO]).",
"uris": null,
"num": null,
"type_str": "figure"
},
"TABREF0": {
"html": null,
"content": "<table><tr><td>INFLESZ</td><td>very difficult 14.9%</td><td>quite difficult 40.4%</td><td>normal 36.2%</td><td>easy 8.5%</td></tr></table>",
"type_str": "table",
"num": null,
"text": "or the INFLESZ tool(Barrio Cantalejo et al., 2008). Most of these tests or formulas are open access and available online, so we could easily apply them to the medical reports we analysed. INFLESZ test results for the CORPUS-ER For example, with one of the most recent test developed for Spanish"
}
}
}
} |