Datasets:
row_idx int64 | f_0 float64 | f_1 string | f_2 string | f_3 string | f_4 string | f_5 string | f_6 string | f_7 string | f_8 string | f_9 string | f_10 string | f_11 string | f_12 string | f_13 string | f_14 string | f_15 string | f_16 string | f_17 float64 | f_18 string | f_19 float64 | f_20 string | f_21 float64 | f_22 string | f_23 float64 | f_24 string | f_25 float64 | f_26 string | target int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3,713 | 68 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.9 | t | 1.9 | t | 108 | t | 1.06 | t | 102 | SVI | 0 |
3,061 | 62 | F | f | f | f | t | f | f | f | f | f | f | f | f | f | f | t | 3.3 | t | 2 | t | 116 | t | 1.06 | t | 110 | SVI | 0 |
1,616 | 34 | F | f | f | f | f | f | f | f | t | f | f | f | f | f | f | t | 0.6 | t | 2.3 | t | 76 | t | 1.05 | t | 73 | other | 0 |
2,110 | 35 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.2 | t | 2.7 | t | 137 | t | 1.19 | t | 115 | SVHC | 0 |
3,683 | 21 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | f | null | f | null | f | null | f | null | other | 0 |
1,163 | 14 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.4 | f | null | t | 91 | t | 0.93 | t | 98 | other | 0 |
942 | 58 | F | f | f | f | f | f | f | f | f | f | t | f | f | f | f | t | 3 | f | null | t | 115 | t | 1.07 | t | 107 | SVI | 0 |
3,624 | 61 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 6.2 | t | 2.3 | t | 118 | t | 1.3 | t | 91 | other | 0 |
2,098 | 54 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 3.3 | f | null | t | 147 | t | 1.07 | t | 138 | other | 0 |
2,470 | 64 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | t | 3.1 | t | 136 | t | 1.07 | t | 127 | other | 0 |
1,916 | 57 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.9 | t | 1.7 | t | 76 | t | 0.81 | t | 93 | SVI | 0 |
887 | 70 | F | f | f | f | t | f | f | f | t | f | f | f | f | f | f | t | 2.1 | t | 1.7 | t | 131 | t | 1 | t | 130 | SVHD | 0 |
2,683 | 57 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.93 | t | 1.3 | t | 90 | t | 1.04 | t | 86 | other | 0 |
685 | 63 | null | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | f | null | f | null | f | null | f | null | other | 0 |
413 | 52 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2 | t | 1.8 | t | 86 | t | 0.86 | t | 101 | other | 0 |
789 | 72 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | t | t | 1.4 | t | 1.6 | t | 118 | t | 1.01 | t | 117 | SVHC | 0 |
2,575 | 57 | M | f | f | f | t | f | f | f | f | f | f | f | f | f | f | t | 0.9 | t | 1.5 | t | 91 | t | 0.78 | t | 116 | other | 0 |
1,627 | 42 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.7 | t | 1.5 | t | 90 | t | 1.14 | t | 79 | other | 0 |
2,725 | 7 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.4 | f | null | t | 155 | t | 0.94 | t | 165 | other | 0 |
2,895 | 64 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 4.6 | t | 1.5 | t | 133 | t | 1.08 | t | 124 | SVI | 0 |
2,117 | 50 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.8 | t | 2 | t | 116 | t | 1.26 | t | 92 | other | 0 |
1,992 | 22 | F | f | f | t | f | f | f | f | f | f | f | f | f | f | f | t | 2 | t | 1.9 | t | 101 | t | 0.92 | t | 109 | other | 0 |
272 | 72 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 5.4 | t | 1 | t | 75 | t | 0.82 | t | 92 | SVI | 1 |
2,651 | 63 | M | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.1 | f | null | t | 80 | t | 0.84 | t | 95 | other | 0 |
521 | 38 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 44 | t | 1.7 | t | 59 | t | 1.04 | t | 57 | other | 0 |
522 | 63 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.9 | f | null | t | 95 | t | 1.08 | t | 88 | SVI | 0 |
2,789 | 54 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | f | null | f | null | f | null | f | null | other | 0 |
350 | 49 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.08 | t | 0.2 | t | 59 | t | 0.79 | t | 74 | SVI | 1 |
1,450 | 52 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 4.7 | t | 2 | t | 19 | t | 1.12 | t | 17 | SVI | 1 |
2,691 | 67 | F | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.015 | t | 4.2 | t | 188 | t | 1.39 | t | 135 | other | 0 |
2,935 | 35 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | f | null | t | 67 | t | 0.9 | t | 75 | other | 0 |
1,873 | 40 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.73 | t | 2 | t | 121 | t | 1.02 | t | 118 | other | 0 |
651 | 72 | F | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.005 | t | 2.5 | t | 231 | t | 0.92 | t | 251 | other | 0 |
1,783 | 30 | F | f | f | f | f | f | f | f | f | f | f | f | t | f | f | t | 0.3 | t | 1.8 | t | 117 | t | 0.97 | t | 121 | SVI | 0 |
3,311 | 70 | null | t | f | f | f | f | f | f | f | t | f | f | f | f | f | t | 0.02 | t | 1.5 | t | 160 | t | 0.94 | t | 171 | other | 0 |
3,492 | 84 | F | f | f | f | f | f | f | f | f | t | f | f | f | f | f | f | null | f | null | t | 88 | t | 0.87 | t | 100 | other | 0 |
3,513 | 34 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.03 | t | 1.6 | t | 96 | t | 0.97 | t | 99 | other | 0 |
3,618 | 75 | F | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.9 | f | null | t | 124 | t | 0.86 | t | 144 | other | 0 |
3,392 | 36 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.4 | t | 3.1 | t | 133 | t | 1.53 | t | 87 | STMW | 0 |
2,726 | 53 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.4 | t | 1.9 | t | 104 | t | 0.93 | t | 112 | SVI | 0 |
168 | 72 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.3 | t | 1.9 | t | 104 | t | 1.01 | t | 104 | SVI | 0 |
3,497 | 45 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.2 | t | 2 | t | 87 | f | null | f | null | other | 0 |
962 | 69 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | f | null | t | 109 | t | 1.03 | t | 106 | other | 0 |
945 | 36 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.1 | t | 2.3 | t | 101 | t | 0.94 | t | 107 | other | 0 |
462 | 27 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.6 | t | 1.9 | t | 119 | t | 0.89 | t | 134 | SVI | 0 |
1,832 | 61 | F | f | f | f | t | f | f | f | f | f | f | f | f | f | f | t | 9.8 | t | 0.4 | t | 81 | t | 0.64 | t | 126 | SVI | 1 |
328 | 73 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.1 | t | 1.5 | t | 77 | t | 0.79 | t | 97 | SVI | 0 |
3,033 | 28 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.2 | t | 1.9 | t | 86 | t | 1.06 | t | 81 | SVHC | 0 |
3,201 | 23 | null | f | f | f | t | f | f | f | f | f | f | f | f | f | f | t | 4.1 | t | 1.9 | t | 66 | t | 0.85 | t | 77 | SVHD | 0 |
367 | 74 | M | t | f | t | f | f | f | f | t | t | f | f | f | f | f | t | 5.2 | f | null | f | null | f | null | f | null | other | 0 |
3,495 | 87 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.2 | t | 0.9 | t | 106 | t | 0.92 | t | 115 | SVI | 1 |
3,180 | 36 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 25 | t | 0.3 | t | 10 | t | 1.18 | t | 8.4 | other | 0 |
2,662 | 83 | null | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 19 | f | null | t | 148 | t | 1.11 | t | 134 | other | 0 |
3,391 | 63 | M | f | f | f | t | f | f | f | f | f | f | f | f | f | f | t | 0.8 | t | 1.9 | t | 98 | t | 0.89 | t | 111 | SVI | 0 |
772 | 33 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.01 | t | 1.5 | t | 160 | t | 0.87 | t | 185 | SVI | 1 |
2,721 | 70 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.1 | t | 2.3 | t | 180 | t | 1.3 | t | 139 | other | 0 |
3,375 | 62 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 4.2 | t | 2.2 | t | 104 | t | 1.11 | t | 93 | other | 0 |
2,965 | 61 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 4.7 | t | 1.1 | t | 89 | t | 0.75 | t | 118 | SVI | 1 |
498 | 55 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 11 | t | 1.5 | t | 144 | t | 1.24 | t | 116 | other | 0 |
2,856 | 77 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.1 | t | 0.8 | t | 99 | t | 0.88 | t | 113 | SVI | 1 |
435 | 42 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.5 | t | 2.1 | t | 121 | t | 1.12 | t | 108 | SVI | 0 |
365 | 50 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 3.1 | t | 1.9 | t | 77 | t | 0.8 | t | 97 | SVI | 0 |
1,220 | 64 | M | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.24 | f | null | t | 83 | t | 0.9 | t | 93 | other | 0 |
276 | 39 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | t | t | 1.5 | f | null | t | 93 | t | 0.75 | t | 125 | SVHC | 0 |
2,494 | 41 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | t | t | 3.1 | t | 2.5 | t | 149 | t | 1.09 | t | 137 | SVHC | 0 |
2,233 | 71 | null | f | f | f | f | f | f | f | f | f | f | f | f | f | t | t | 1.1 | t | 2.4 | t | 122 | t | 1.12 | t | 109 | other | 0 |
1,517 | 53 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 4.3 | t | 1.5 | t | 94 | t | 0.88 | t | 107 | SVI | 0 |
407 | 34 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | t | t | 0.83 | t | 2.4 | t | 114 | t | 1.02 | t | 112 | SVHC | 0 |
2,620 | 71 | F | f | f | f | f | f | t | f | f | f | f | f | f | f | f | t | 0.01 | f | null | t | 146 | t | 0.93 | t | 156 | other | 0 |
3,015 | 36 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.9 | t | 1.4 | t | 92 | t | 0.92 | t | 101 | SVI | 0 |
844 | 53 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.3 | t | 1.2 | t | 105 | t | 0.91 | t | 115 | SVHC | 0 |
1,950 | 33 | F | f | f | f | f | f | f | f | f | f | f | t | f | f | f | t | 0.08 | f | null | t | 126 | t | 1 | t | 126 | other | 0 |
1,288 | 74 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.61 | t | 0.9 | t | 115 | t | 0.75 | t | 153 | SVI | 1 |
1,922 | 19 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.2 | t | 2.3 | t | 91 | t | 0.93 | t | 98 | SVHC | 0 |
1,786 | 60 | M | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.35 | t | 1.6 | t | 98 | t | 0.75 | t | 131 | other | 0 |
1,830 | 18 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.9 | t | 3 | t | 143 | t | 1.32 | t | 108 | other | 0 |
1,506 | 58 | F | f | f | f | f | f | f | f | t | f | f | f | f | f | f | t | 1.3 | t | 1.9 | t | 66 | t | 0.96 | t | 68 | other | 0 |
1,313 | 51 | M | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.4 | t | 2.6 | t | 118 | t | 0.91 | t | 130 | SVHC | 0 |
1,966 | 67 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.8 | t | 2.3 | t | 104 | t | 1.04 | t | 100 | SVI | 0 |
855 | 43 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | f | null | f | null | f | null | f | null | f | null | other | 0 |
2,091 | 36 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.25 | t | 2.5 | t | 102 | t | 0.96 | t | 106 | other | 0 |
78 | 61 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.61 | t | 1.6 | t | 103 | t | 0.93 | t | 111 | SVI | 0 |
944 | 28 | F | f | f | f | f | f | t | f | f | f | f | f | f | f | f | t | 103 | t | 2.1 | t | 65 | t | 1.16 | t | 56 | SVI | 0 |
199 | 32 | F | t | f | f | f | t | f | f | f | t | f | f | f | f | f | t | 0.025 | t | 3.7 | t | 139 | t | 1.34 | t | 104 | other | 0 |
1,533 | 52 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.9 | t | 2 | t | 73 | t | 1.04 | t | 70 | other | 0 |
2,155 | 47 | M | f | f | f | t | f | f | f | f | f | f | f | f | f | f | t | 1.1 | f | null | t | 94 | t | 0.97 | t | 97 | SVI | 0 |
801 | 22 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 5.6 | t | 3 | t | 123 | t | 1.22 | t | 101 | SVI | 0 |
2,269 | 44 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.8 | t | 2.3 | t | 129 | t | 1.24 | t | 103 | SVHC | 0 |
2,225 | 53 | M | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.5 | t | 2.8 | t | 130 | t | 1.01 | t | 128 | other | 0 |
1,582 | 73 | F | f | f | f | f | f | f | f | f | t | f | f | f | f | f | t | 2 | t | 1.6 | t | 116 | t | 0.93 | t | 125 | SVI | 0 |
231 | 70 | M | f | f | f | f | f | f | f | f | t | f | f | f | f | f | f | null | f | null | f | null | f | null | f | null | other | 0 |
3,549 | 16 | F | f | f | f | f | f | t | f | f | f | f | f | f | f | f | t | 30 | t | 1.2 | t | 30 | t | 1.45 | t | 21 | other | 0 |
3,476 | 35 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 2.3 | t | 2.3 | t | 83 | t | 1.19 | t | 69 | SVHC | 0 |
2,716 | 60 | F | f | f | f | f | f | f | f | f | t | f | f | f | f | f | t | 0.025 | t | 3.9 | t | 123 | t | 0.98 | t | 126 | other | 0 |
2,095 | 64 | M | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.8 | t | 1.4 | t | 117 | t | 0.97 | t | 121 | other | 0 |
2,118 | 25 | F | f | f | f | f | f | f | f | f | f | f | f | t | f | f | t | 0.53 | t | 1.8 | t | 107 | t | 0.93 | t | 115 | other | 0 |
3,046 | 56 | F | t | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.3 | t | 2.8 | t | 141 | t | 0.99 | t | 142 | other | 0 |
2,172 | 38 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 0.1 | t | 1.5 | t | 106 | t | 0.79 | t | 134 | SVI | 0 |
2,328 | 74 | F | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.3 | t | 1.9 | t | 99 | t | 1.12 | t | 88 | other | 0 |
3,600 | 22 | M | f | f | f | f | f | f | f | f | f | f | f | f | f | f | t | 1.7 | t | 2.3 | t | 127 | t | 1 | t | 127 | other | 0 |
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sick
Part of TabBioMed (TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning), a benchmark of 94 curated biomedical tabular datasets. Code, preprocessing and documentation: https://github.com/AI-sandbox/TabBioMed.
OpenML dataset (ID 38), relation: sick
| Domain | Task | Samples | Features | Classes |
|---|---|---|---|---|
| Clinical & Healthcare | binary | 3,772 | 27 | 2 |
Splits. Fixed train/val/test split (2642/565/565 rows).
Files
data/**.parquet: one row per sample.row_idxis the row index in the original TabBioMed array;f_<i>[_<name>]are the features (in order);target(ortarget_<j>for multi-target tasks) is the label. Categorical feature indices (0-based, among the features):[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 24, 26]. Missing values are stored as nulls.metadata.json: TabBioMed task metadata (task type, categorical indices, source, description).
from datasets import load_dataset
ds = load_dataset("TabBioMed/sick")
A Croissant (1.1) description with Responsible-AI fields is distributed with the TabBioMed release.
Source and license
Source: OpenML_Dataset_ID_38
This derived dataset is distributed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Please also cite and respect the terms of the original source.
Citation
@inproceedings{tabbiomed2026,
title = {TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning},
author = {Mateo Bernad{\'o}, Pau and Polapragada, Saivenkata Nagavyjayanthi and Bonet, David and Arbiol Rakuljic, Pol and Mogas Pladevall, Laia and Comajoan Cara, Mar{\c{c}}al and Gonzalez Ferrer, Jesus and Abante, Jordi and Mas Montserrat, Daniel and Haussler, David and Ioannidis, Alexander G.},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track},
year = {2026}
}
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