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"abstract": "One of many challenges in cross-view gait recognition is that a pedestrian's gaits have huge visual differences under different views. A promising solution to this challenge is to extract fundamental discriminative view-invariant gait features, so that gait recognition systems can be robust to viewpoint varying. In order to extract discriminative gait features, this paper proposes a method to decompose identity and view for cross-view gait recognition. Our method employs a newly designed auto-encoder to detach the identity features from the view features. We train our model with the classification and metric learning to obtain discriminative identity feature. Also, both the view regression and identity ambiguity are applied to ensure that the view features only contain view information. Finally, a dissimilarity loss is proposed to increase the distribution discrepancy between identity feature and view feature, so as to further refine the identity feature. The experimental results on the CASIA-B and OU-ISIR databases show that the proposed method performs well in cross-view gait recognition.",
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"abstract": "We present initial results of a quantitative analysis of how developers layout the visualisations in their multiple view systems. Many developers create multiple view systems and the technique is commonly used by the visualisation community. Each visualisation shows data in a different way, and often user interaction is coordinated between the views. But it is not always clear to know how many views a developer should use, or what would be the best layout. We extract images of visualisation tools, across TVCG journal, conference, posters and workshop papers 2012-2018 to analyse the quantity and layout of the views in these visualisation systems. Focusing on view juxtaposition, we code the layout of 491 images and analyse view topology in juxtaposed views. Our analysis acts as a starting point to help designers create better visualisations, acts as a taxonomy of visualisation layouts, and provides a quantitative analysis of how many views developers have used in their visualisation systems.",
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"abstract": "The grain size dependence of electrolytic properties in 25 at.% yttrium doped ceria was investigated. The sintered bodies were prepared from fine Y0.25Ce0.75O1.875 powders synthesized by carbonate co-precipitation method. By using sintering temperature in range of 950deg-1400degC, the average grain size of electrolytes varied from 90 nm to 0.9 mum. The conductivity of samples with different grain size was determined by dc three-point measurements at 400degC-600degC. Then the activation energy was calculated from the data of electrical conductivity. Grain-size dependence was observed on the plots of conductivity vs. average grain size. As the grain size decreased from 0.9 mum to 0.3 mum, the conductivity decreased and the activation energy increased. This result was consistent with previous reports and could be explained by the space-charge-layer model. However, the conductivity increased while the grain size decreased from 0.3 mum to 90 nm. Correspondingly, the activation energy decreased. To clarify the mechanism of this phenomenon, the microstructure of samples was observed using TEM. Nano-sized domains inside the grains were observed on the high resolution images. Their size and amount were reduced as the grain size decreased. It is possible that the abnormal increase in conductivity at fine grain size (<0.3 mum) was partly contributed by the changes in nano-sized domains",
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"content": "The grain size dependence of electrolytic properties in 25 at.% yttrium doped ceria was investigated. The sintered bodies were prepared from fine Y0.25Ce0.75O1.875 powders synthesized by carbonate co-precipitation method. By using sintering temperature in range of 950deg-1400degC, the average grain size of electrolytes varied from 90 nm to 0.9 mum. The conductivity of samples with different grain size was determined by dc three-point measurements at 400degC-600degC. Then the activation energy was calculated from the data of electrical conductivity. Grain-size dependence was observed on the plots of conductivity vs. average grain size. As the grain size decreased from 0.9 mum to 0.3 mum, the conductivity decreased and the activation energy increased. This result was consistent with previous reports and could be explained by the space-charge-layer model. However, the conductivity increased while the grain size decreased from 0.3 mum to 90 nm. Correspondingly, the activation energy decreased. To clarify the mechanism of this phenomenon, the microstructure of samples was observed using TEM. Nano-sized domains inside the grains were observed on the high resolution images. Their size and amount were reduced as the grain size decreased. It is possible that the abnormal increase in conductivity at fine grain size (<0.3 mum) was partly contributed by the changes in nano-sized domains",
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"normalizedAbstract": "The grain size dependence of electrolytic properties in 25 at.% yttrium doped ceria was investigated. The sintered bodies were prepared from fine Y0.25Ce0.75O1.875 powders synthesized by carbonate co-precipitation method. By using sintering temperature in range of 950deg-1400degC, the average grain size of electrolytes varied from 90 nm to 0.9 mum. The conductivity of samples with different grain size was determined by dc three-point measurements at 400degC-600degC. Then the activation energy was calculated from the data of electrical conductivity. Grain-size dependence was observed on the plots of conductivity vs. average grain size. As the grain size decreased from 0.9 mum to 0.3 mum, the conductivity decreased and the activation energy increased. This result was consistent with previous reports and could be explained by the space-charge-layer model. However, the conductivity increased while the grain size decreased from 0.3 mum to 90 nm. Correspondingly, the activation energy decreased. To clarify the mechanism of this phenomenon, the microstructure of samples was observed using TEM. Nano-sized domains inside the grains were observed on the high resolution images. Their size and amount were reduced as the grain size decreased. It is possible that the abnormal increase in conductivity at fine grain size (<0.3 mum) was partly contributed by the changes in nano-sized domains",
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"abstract": "Although it is well known that the enforced flow of dielectric liquids over a solid interface can give rise to charge separation with the resulting accumulation of static charges, the underlying physics is complex. The incidence of streaming electrification in large transformers (and other industrial equipment) has generated the need for both an understanding and mathematical description of the physics. Modelling of the phenomena is needed since the mechanisms do not readily scale so that small-scale laboratory experiments cannot be used to predict performance. This contribution chronicles the development of both steady-state and transient descriptions of the streaming electrification process. The nature of the phenomenon is such that appropriate assumptions and approximations need to be made. As a consequence, it is also important to include some experimental verification of the outcomes; at least in qualitative form. The entrainment of charge from the interface Helmholtz layer also intimately involves the flow of the liquid. A description of the flow regimes and a transient solution of the flow through a duct are thus an integral part of the modelling effort The utility of the steady-state model developed is demonstrated by application to an oil-cellulose system typical of a large core-form transformer. The method advocated takes advantage of the repeat duct arrangement in such units. The results presented allow the internal behaviour of such a unit to be studied in considerable depth, and provide insight into the complex interplay between generation and relaxation in circumstances when flow rates, temperature, external fields and influent charge are changed.",
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"title": "Electrical properties of fluorinated gel electrolytes using conducting solution and its application to secondary battery",
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"abstract": "The lithium ionic electrolytes of fluorinated gel materials have been found to show high ionic conductivity. We proposed the application to a lithium ion secondary battery using this gel electrolyte. Non-crosslinked fluorinated gel materials were prepared by reacting fluoroalkanoyl peroxides with 2-acrylamid-2-methylpropanesulfonic acid (AMPS) oligomer, or 2-glucosyloxyyethyl methacrylate (GEMA) oligomer containing fluoroalkylated end-capped units {[-RF-(AMPS)q]p-}. Three kinds of lithium salts [LiBF/sub 6/, LiCF/sub 3/SO/sub 3/, and LiN(CF/sub 3/-SO/sub 2/)/sub 2/] were used for ionic electrolyte of fluorinated gel materials. The ionic conductivity of gel electrolytes depended on the oligomer materials, the lithium salts and its concentration. The conductivity of fluoroalkylated gel electrolyte using GEMA oligomer was larger than AMPS oligomer. When the lithium salts were LiN(CF/sub 3/SO/sub 2/)/sub 2/ and concentration of 5.3 mmol/g in the case of GEMA gel electrolytes, the conductivity was 4.5 /spl times/ 10/sup -3/ S/cm. However, the highest conductivity was obtained for AMPS gel electrolyte produced by ionic solution. The conductivity was 1.2 /spl times/ 10/sup -2/ S/cm, We also measured the charge and discharge characteristics of the lithium ion secondary batteries that were fabricated by a constitution of carbon negative electrode, fluorinated gel electrolyte with LiN(CF/sub 3/SO/sub 2/)/sub 2/ and positive electrode of LiCoO/sub 2/.",
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{
"abstractType": "Regular",
"content": "The lithium ionic electrolytes of fluorinated gel materials have been found to show high ionic conductivity. We proposed the application to a lithium ion secondary battery using this gel electrolyte. Non-crosslinked fluorinated gel materials were prepared by reacting fluoroalkanoyl peroxides with 2-acrylamid-2-methylpropanesulfonic acid (AMPS) oligomer, or 2-glucosyloxyyethyl methacrylate (GEMA) oligomer containing fluoroalkylated end-capped units {[-RF-(AMPS)q]p-}. Three kinds of lithium salts [LiBF/sub 6/, LiCF/sub 3/SO/sub 3/, and LiN(CF/sub 3/-SO/sub 2/)/sub 2/] were used for ionic electrolyte of fluorinated gel materials. The ionic conductivity of gel electrolytes depended on the oligomer materials, the lithium salts and its concentration. The conductivity of fluoroalkylated gel electrolyte using GEMA oligomer was larger than AMPS oligomer. When the lithium salts were LiN(CF/sub 3/SO/sub 2/)/sub 2/ and concentration of 5.3 mmol/g in the case of GEMA gel electrolytes, the conductivity was 4.5 /spl times/ 10/sup -3/ S/cm. However, the highest conductivity was obtained for AMPS gel electrolyte produced by ionic solution. The conductivity was 1.2 /spl times/ 10/sup -2/ S/cm, We also measured the charge and discharge characteristics of the lithium ion secondary batteries that were fabricated by a constitution of carbon negative electrode, fluorinated gel electrolyte with LiN(CF/sub 3/SO/sub 2/)/sub 2/ and positive electrode of LiCoO/sub 2/.",
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"High Ionic Conductivity",
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"1 Ethyl 3 Methylimidazolium Tetrafluoroborate",
"Complex Impedance Analysis",
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"Conductivity",
"Lithium",
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"affiliation": "Dept. of Electr. Eng., Nara Nat. Coll. of Technol., Japan",
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"affiliation": "Dept. of Electr. Eng., Nara Nat. Coll. of Technol., Japan",
"fullName": "T. Minami",
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"affiliation": "Dept. of Electr. Eng., Nara Nat. Coll. of Technol., Japan",
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"title": "Surface conductivity in liquid-solid interface due to image force",
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"abstract": "The image force is considered to be one of the nonspecific sources of surface conductivity origin in the interface between a non-polar liquid dielectric and a polar solid one. Two possible physical mechanisms have been investigated. The first one takes into account the existence of a potential barrier to the charge movement as it leaves the surface. Therefore the charges that are in liquid are attracted to the surface. The second one is the reduction of dissociation energy of ion pairs close to the interface in comparison with bulk dissociation. Both mechanisms result in a decrease of recombination rate and in a sharp increase of dissociation rate. It has been shown that both these mechanisms could lead to creation and accumulation of an abnormal nonspecific surface charge carrier. Preliminary experimental results don't contradict theory. Surface conductivity of ceramics with /spl epsiv/=80 in contact with transformer oil (/spl epsiv/=2.3) is sharply increased in case of slight dissociating organic doping.",
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"content": "The image force is considered to be one of the nonspecific sources of surface conductivity origin in the interface between a non-polar liquid dielectric and a polar solid one. Two possible physical mechanisms have been investigated. The first one takes into account the existence of a potential barrier to the charge movement as it leaves the surface. Therefore the charges that are in liquid are attracted to the surface. The second one is the reduction of dissociation energy of ion pairs close to the interface in comparison with bulk dissociation. Both mechanisms result in a decrease of recombination rate and in a sharp increase of dissociation rate. It has been shown that both these mechanisms could lead to creation and accumulation of an abnormal nonspecific surface charge carrier. Preliminary experimental results don't contradict theory. Surface conductivity of ceramics with /spl epsiv/=80 in contact with transformer oil (/spl epsiv/=2.3) is sharply increased in case of slight dissociating organic doping.",
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"abstract": "This paper is aimed at the influence of the hydrostatic pressure on the discharge propagating at the liquid/solid insulating interfaces under AC and DC voltages using a point-plane electrode arrangement. It is shown that different shapes of creepage discharges and associated currents can be initiated for the same experimental conditions indicating the existence of different propagation modes of discharges. On the other hand, the final length and the number of creepage discharge branches, the corresponding currents and the light emitted are reduced when a hydrostatic pressure is applied; this indicates the implication of gaseous processes in the creepage discharge phenomena. The final length of discharges increases quasi-linearly with the voltage, whatever the type (DC or AC) and polarity of the voltage, and decreases quasi-linearly when the pressure increases.",
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"content": "This paper is aimed at the influence of the hydrostatic pressure on the discharge propagating at the liquid/solid insulating interfaces under AC and DC voltages using a point-plane electrode arrangement. It is shown that different shapes of creepage discharges and associated currents can be initiated for the same experimental conditions indicating the existence of different propagation modes of discharges. On the other hand, the final length and the number of creepage discharge branches, the corresponding currents and the light emitted are reduced when a hydrostatic pressure is applied; this indicates the implication of gaseous processes in the creepage discharge phenomena. The final length of discharges increases quasi-linearly with the voltage, whatever the type (DC or AC) and polarity of the voltage, and decreases quasi-linearly when the pressure increases.",
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"keywords": [
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"Hydrostatics",
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"Voltage",
"Electrodes",
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"Dielectric Liquids",
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"title": "2018 International Conference on Intelligent Circuits and Systems (ICICS)",
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"abstract": "In this research, new film of a free-standing electrolyte containing Poly (ethyl methacrylate) (PEMA), Ethylene carbonate (EC) blends as a host for the electrolyte which was doped with Sodium Iodide (NaI) as the dopant salt and CdS nanoparticles as nanofillers was successfully prepared by solution casting technique. The polymer electrolyte of PEMANaI-EC-CdS was characterized using impedance spectroscopy (EIS), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). From the EIS results, it showed that electrolyte exhibited the highest ionic conductivity of 6.2×10-4Scm-1at the 9% concentration of CdS nano-particles. The ionic conductivity result was supported by the morphological studies which revealed some dark pores which indicates the material is amorphous at room temperature because of ethylene carbonate. The features of complexation of the electrolytes were studied by FTIR.",
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"content": "In this research, new film of a free-standing electrolyte containing Poly (ethyl methacrylate) (PEMA), Ethylene carbonate (EC) blends as a host for the electrolyte which was doped with Sodium Iodide (NaI) as the dopant salt and CdS nanoparticles as nanofillers was successfully prepared by solution casting technique. The polymer electrolyte of PEMANaI-EC-CdS was characterized using impedance spectroscopy (EIS), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). From the EIS results, it showed that electrolyte exhibited the highest ionic conductivity of 6.2×10-4Scm-1at the 9% concentration of CdS nano-particles. The ionic conductivity result was supported by the morphological studies which revealed some dark pores which indicates the material is amorphous at room temperature because of ethylene carbonate. The features of complexation of the electrolytes were studied by FTIR.",
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"normalizedAbstract": "In this research, new film of a free-standing electrolyte containing Poly (ethyl methacrylate) (PEMA), Ethylene carbonate (EC) blends as a host for the electrolyte which was doped with Sodium Iodide (NaI) as the dopant salt and CdS nanoparticles as nanofillers was successfully prepared by solution casting technique. The polymer electrolyte of PEMANaI-EC-CdS was characterized using impedance spectroscopy (EIS), scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). From the EIS results, it showed that electrolyte exhibited the highest ionic conductivity of 6.2×10-4Scm-1at the 9% concentration of CdS nano-particles. The ionic conductivity result was supported by the morphological studies which revealed some dark pores which indicates the material is amorphous at room temperature because of ethylene carbonate. The features of complexation of the electrolytes were studied by FTIR.",
"fno": "648300a201",
"keywords": [
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"Electrochemical Impedance Spectroscopy",
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"abstract": "Calcium phosphate bioceramics are used widely as bone scaffold materials. To understand the process of protein adsorption on the surface of bioceramics, in the paper a Cellular Automata model is provided to simulate it. The model is concerned with the study of two-dimensional protein adsorption, considering the pore size, interconnectivity and the adsorption probability and desorption probability of proteins. Three simulation steps focusing on porous structures, body fluid flow in porous bioceramics and protein adsorption on the surface of bioceramics are discussed. The simulation results show the curves of proteins adsorbed on the surface of bioceramics vs. time are coincident with the results of the experiments in vitro",
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"abstract": "This paper proposes a quality detection method of LED surface defects in dispensing back-end based on computer vision library HALCON. The key steps mainly include image preprocessing, image matching and defect detection, etc. Firstly, to choose the matching area automatically according to the regional characteristics of the LED chip. Secondly, image matching with standard template. Finally, complete defect detection using the improved matching algorithm. The method can select matching area automatically from the collection of image with CMOS. It can complete image matching quickly and accurately, and detect the defect effectively.",
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"abstract": "In this paper we present an improvement to the fictitious magnetic charge approach to computing inductances in the presence of permeable materials. The improvement replaces integration over a \"non-piercing\" surface with a line integral and an efficient quadrature scheme. Eliminating the need to generate non-piercing surfaces substantially simplifies handling problems with general geometries of permeable materials. Computational results are presented to demonstrate the accuracy and versatility of the new method.",
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"content": "In this paper we present an improvement to the fictitious magnetic charge approach to computing inductances in the presence of permeable materials. The improvement replaces integration over a \"non-piercing\" surface with a line integral and an efficient quadrature scheme. Eliminating the need to generate non-piercing surfaces substantially simplifies handling problems with general geometries of permeable materials. Computational results are presented to demonstrate the accuracy and versatility of the new method.",
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"abstract": "Information graphics, such as graphs and plots, are used in technical documents to convey information to humans and to facilitate greater understanding. Usually, graphics are a key component in a technical document, as they enable the author to convey complex ideas in a simplified visual format. However, in an automatic text recognition system, which are typically used to digitize documents, the ideas conveyed in a graphical format are lost. We contend that the message or extracted information can be used to help better understand the ideas conveyed in the document. In scientific papers, line plots are the most commonly used graphic to represent experimental results in the form of correlation present between values represented on the axes. The contribution of our work is in the series of image processing algorithms that are used to automatically extract relevant information, including text and plot from graphics found in technical documents. We validate the approach by performing the experiments on a dataset of line plots obtained from scientific documents from computer science conference papers and evaluate the variation of a reconstructed curve from the original curve. Our algorithm achieves a classification accuracy of 91% across the dataset and successfully extracts the axes from 92% of line plots. Axes label extraction and line curve tracing are performed successfully in about half the line plots as well.",
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"abstract": "Datasets obtained through recently advanced measurement techniques tend to possess a large number of dimensions. This leads to explosively increasing computation costs for analyzing such datasets, thus making formulation and verification of scientific hypotheses very difficult. Therefore, an efficient approach to identifying feature subspaces of target datasets, that is, the subspaces of dimension variables or subsets of the data samples, is required to describe the essence hidden in the original dataset. This paper proposes a visual data mining framework for supporting semiautomatic data analysis that builds upon asymmetric biclustering to explore highly correlated feature subspaces. For this purpose, a variant of parallel coordinate plots, many-to-many parallel coordinate plots, is extended to visually assist appropriate selections of feature subspaces as well as to avoid intrinsic visual clutter. In this framework, biclustering is applied to dimension variables and data samples of the dataset simultaneously and asymmetrically. A set of variable axes are projected to a single composite axis while data samples between two consecutive variable axes are bundled using polygonal strips. This makes the visualization method scalable and enables it to play a key role in the framework. The effectiveness of the proposed framework has been empirically proven, and it is remarkably useful for many-to-many parallel coordinate plots.",
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"abstract": "In this paper we describe a battlefield visualization system, called Dragon, which we have implemented on a virtual reality responsive workbench. The Dragon system has been successfully deployed as part of two large military exercises: the Hunter Warrior advanced warfighting experiment, in March 1997, and the Joint Counter Mine advanced concept tactical demonstration, in August and September 1997. We describe battlefield visualization, the Dragon system, and the workbench, and we describe our experiences as part of these two real-world deployments, with an emphasis on lessons learned and needed future work.",
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"abstract": "The endoscopic-assisted neck minimally invasive thyroid surgery is one of the main directions of development of thyroid surgery in recent years. To retrospectively analyze clinical data of 402 cases (327 women and 75 men with a mean age of 44 years) of endoscopic-assisted neck minimally invasive radical operation of thyroid cancer in The First Hospital of Jilin University in China from January, 2007 to May, 2015. The operation was performed under general anesthesia and tracheal intubation, and the Miccoli's technique was performed during the surgery. 381 patients were successfully operated by endoscopic-assisted neck minimally invasive radical operation of thyroid cancer. 21 cases transferred to open surgery because of extensive adhesion of tumor or uncontrollable bleeding. All cases had no postoperative bleeding or infection. Normal endocrine suppression therapy were offered after operation and some patients were undergone the treatment of I131. The whole group were followed up for 1 to 36 months, no recurrences happened. Endoscopic-assisted neck minimally invasive radical operation of differentiated thyroid cancer is a practical, low invasive surgery, which has advantages of safety, reliability, less bleeding, less pain, shorter hospital stay, fewer complications and relative cosmetic results. On the basis of mastering certain skills, it has better clinical effects and brighter application prospect.",
"abstracts": [
{
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"content": "The endoscopic-assisted neck minimally invasive thyroid surgery is one of the main directions of development of thyroid surgery in recent years. To retrospectively analyze clinical data of 402 cases (327 women and 75 men with a mean age of 44 years) of endoscopic-assisted neck minimally invasive radical operation of thyroid cancer in The First Hospital of Jilin University in China from January, 2007 to May, 2015. The operation was performed under general anesthesia and tracheal intubation, and the Miccoli's technique was performed during the surgery. 381 patients were successfully operated by endoscopic-assisted neck minimally invasive radical operation of thyroid cancer. 21 cases transferred to open surgery because of extensive adhesion of tumor or uncontrollable bleeding. All cases had no postoperative bleeding or infection. Normal endocrine suppression therapy were offered after operation and some patients were undergone the treatment of I131. The whole group were followed up for 1 to 36 months, no recurrences happened. Endoscopic-assisted neck minimally invasive radical operation of differentiated thyroid cancer is a practical, low invasive surgery, which has advantages of safety, reliability, less bleeding, less pain, shorter hospital stay, fewer complications and relative cosmetic results. On the basis of mastering certain skills, it has better clinical effects and brighter application prospect.",
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"normalizedAbstract": "The endoscopic-assisted neck minimally invasive thyroid surgery is one of the main directions of development of thyroid surgery in recent years. To retrospectively analyze clinical data of 402 cases (327 women and 75 men with a mean age of 44 years) of endoscopic-assisted neck minimally invasive radical operation of thyroid cancer in The First Hospital of Jilin University in China from January, 2007 to May, 2015. The operation was performed under general anesthesia and tracheal intubation, and the Miccoli's technique was performed during the surgery. 381 patients were successfully operated by endoscopic-assisted neck minimally invasive radical operation of thyroid cancer. 21 cases transferred to open surgery because of extensive adhesion of tumor or uncontrollable bleeding. All cases had no postoperative bleeding or infection. Normal endocrine suppression therapy were offered after operation and some patients were undergone the treatment of I131. The whole group were followed up for 1 to 36 months, no recurrences happened. Endoscopic-assisted neck minimally invasive radical operation of differentiated thyroid cancer is a practical, low invasive surgery, which has advantages of safety, reliability, less bleeding, less pain, shorter hospital stay, fewer complications and relative cosmetic results. On the basis of mastering certain skills, it has better clinical effects and brighter application prospect.",
"fno": "8302a264",
"keywords": [
"Neck",
"Cancer",
"Minimally Invasive Surgery",
"Tumors",
"Hemorrhaging",
"Glands",
"Radical Operation",
"Thyroid Cancer",
"Endoscope"
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{
"affiliation": null,
"fullName": "Su Dong",
"givenName": "Su",
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"fullName": "Meng Jin",
"givenName": "Meng",
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{
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"fullName": "Guang Chen",
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"surname": "Chen",
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{
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"fullName": "Jia Liu",
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"abstract": "Skin injury is a common side effect of breast-cancer radiation therapy. Although physicians often observe skin toxicity, quantifying its severity remains a challenge. We present a novel quantitative ultrasonic technique to evaluate skin changes associated with radiotherapy. An in vivo study with twelve breast-cancer patients was conducted. All patients received a standard course of post-surgery radiation therapy. Each patient received ultrasound scans to the irradiated breast and the untreated (contra-lateral) breast. Radio-frequency (RF) backscatter signals and B-mode images were acquired simultaneously. To quantify the severity of skin injury, two metrics were calculated from the RF signals: skin thickness and Pearson correlation coefficient of the subcutaneous layer. Comparing to the non-irradiated skin, the average thickness of the irradiated skin increased by 40% (p=0.005) and the average correlation coefficient of the irradiated hypodermis decreased by 35% (p=0.02). This study demonstrates the feasibility of using a non-invasive ultrasonic technique to detect and quantify radiation-induced skin changes.",
"abstracts": [
{
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"content": "Skin injury is a common side effect of breast-cancer radiation therapy. Although physicians often observe skin toxicity, quantifying its severity remains a challenge. We present a novel quantitative ultrasonic technique to evaluate skin changes associated with radiotherapy. An in vivo study with twelve breast-cancer patients was conducted. All patients received a standard course of post-surgery radiation therapy. Each patient received ultrasound scans to the irradiated breast and the untreated (contra-lateral) breast. Radio-frequency (RF) backscatter signals and B-mode images were acquired simultaneously. To quantify the severity of skin injury, two metrics were calculated from the RF signals: skin thickness and Pearson correlation coefficient of the subcutaneous layer. Comparing to the non-irradiated skin, the average thickness of the irradiated skin increased by 40% (p=0.005) and the average correlation coefficient of the irradiated hypodermis decreased by 35% (p=0.02). This study demonstrates the feasibility of using a non-invasive ultrasonic technique to detect and quantify radiation-induced skin changes.",
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"normalizedAbstract": "Skin injury is a common side effect of breast-cancer radiation therapy. Although physicians often observe skin toxicity, quantifying its severity remains a challenge. We present a novel quantitative ultrasonic technique to evaluate skin changes associated with radiotherapy. An in vivo study with twelve breast-cancer patients was conducted. All patients received a standard course of post-surgery radiation therapy. Each patient received ultrasound scans to the irradiated breast and the untreated (contra-lateral) breast. Radio-frequency (RF) backscatter signals and B-mode images were acquired simultaneously. To quantify the severity of skin injury, two metrics were calculated from the RF signals: skin thickness and Pearson correlation coefficient of the subcutaneous layer. Comparing to the non-irradiated skin, the average thickness of the irradiated skin increased by 40% (p=0.005) and the average correlation coefficient of the irradiated hypodermis decreased by 35% (p=0.02). This study demonstrates the feasibility of using a non-invasive ultrasonic technique to detect and quantify radiation-induced skin changes.",
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"Breast Cancer",
"Radiotherapy",
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"fullName": "Tian Liu",
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"title": "Smart-phone based monitoring of cancer related fatigue",
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"abstract": "Cancer related fatigue is a chronic disease that may persist up to 10 years after treatment of cancer has been finished successfully and is one of the most prevalent problems of cancer survivors. Cancer related fatigue is a complex symptom that is not sufficiently understood and difficult to remedy. Patients do not necessarily follow a treatment plan with regular in-office follow-ups. As a consequence, physicians lack of knowledge how their patients are coping with their fatigue in daily life. To overcome the resulting knowledge gap, we developed a smart-phone based monitoring system providing activity data from smart-phone sensors. Furthermore, based on self-reports following the experience based sampling method, the app asks the patients to report their perceived degree of fatigue and interference of fatigue with daily life by means of digital questionnaires. To evaluate the monitoring system in an observational study, we recruited 7 patients suffering from cancer related fatigue and tracked them over 2 to 3 weeks. We collected about 2700 hours of activity data and over 500 completed questionnaires. Based on this study, we conclude that our monitoring system can be used in a clinical trial to examine cancer related fatigue.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cancer related fatigue is a chronic disease that may persist up to 10 years after treatment of cancer has been finished successfully and is one of the most prevalent problems of cancer survivors. Cancer related fatigue is a complex symptom that is not sufficiently understood and difficult to remedy. Patients do not necessarily follow a treatment plan with regular in-office follow-ups. As a consequence, physicians lack of knowledge how their patients are coping with their fatigue in daily life. To overcome the resulting knowledge gap, we developed a smart-phone based monitoring system providing activity data from smart-phone sensors. Furthermore, based on self-reports following the experience based sampling method, the app asks the patients to report their perceived degree of fatigue and interference of fatigue with daily life by means of digital questionnaires. To evaluate the monitoring system in an observational study, we recruited 7 patients suffering from cancer related fatigue and tracked them over 2 to 3 weeks. We collected about 2700 hours of activity data and over 500 completed questionnaires. Based on this study, we conclude that our monitoring system can be used in a clinical trial to examine cancer related fatigue.",
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"normalizedAbstract": "Cancer related fatigue is a chronic disease that may persist up to 10 years after treatment of cancer has been finished successfully and is one of the most prevalent problems of cancer survivors. Cancer related fatigue is a complex symptom that is not sufficiently understood and difficult to remedy. Patients do not necessarily follow a treatment plan with regular in-office follow-ups. As a consequence, physicians lack of knowledge how their patients are coping with their fatigue in daily life. To overcome the resulting knowledge gap, we developed a smart-phone based monitoring system providing activity data from smart-phone sensors. Furthermore, based on self-reports following the experience based sampling method, the app asks the patients to report their perceived degree of fatigue and interference of fatigue with daily life by means of digital questionnaires. To evaluate the monitoring system in an observational study, we recruited 7 patients suffering from cancer related fatigue and tracked them over 2 to 3 weeks. We collected about 2700 hours of activity data and over 500 completed questionnaires. Based on this study, we conclude that our monitoring system can be used in a clinical trial to examine cancer related fatigue.",
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"authors": [
{
"affiliation": "Wearable Computing Lab, ETH Zürich, Zurich, Switzerland",
"fullName": "Vanessa C. Klaas",
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"affiliation": "University Hospital Zurich, Zurich, Switzerland",
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"affiliation": "University Hospital Zurich, Zurich, Switzerland",
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"abstract": "Previous advanced radiation therapy (RT) techniques for early stage glottic cancer attempted to spare the normal tissue. We aimed to evaluate the dosimetric advantages of intensity modulated arc therapy (IMAT) in terms of increase target tumor dose and sparing normal tissue hand-dose in early-stage glottic cancer patients. In our previous published paper, we explored the application of conventional linear accelerator IMAT technology in large-scale tumors of cervical cancer and elongate target areas of esophageal cancer.The purpose of this study is to investigate using constant dose rate IMAT on conventional linear accelerator, by comparing with the IMRT technology to evaluate the performance of IMAT on early-stage glottic carcinoma patients and then provide guidance for clinical treatment. The results show that glottic carcinoma can be implemented IMAT plans on conventional Linac for smoothly and quickly at busy cancer center. IMAT planning can meet the clinical demand, showed significant dosimetric benefits in sparing both the thyroid gland and carotid artery. Compared with IMRT, IMAT plan has more MUs and less treatment time and significantly improves the treatment efficiency.An evaluation of weight loss must be performed during treatment for IMAT patients.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Previous advanced radiation therapy (RT) techniques for early stage glottic cancer attempted to spare the normal tissue. We aimed to evaluate the dosimetric advantages of intensity modulated arc therapy (IMAT) in terms of increase target tumor dose and sparing normal tissue hand-dose in early-stage glottic cancer patients. In our previous published paper, we explored the application of conventional linear accelerator IMAT technology in large-scale tumors of cervical cancer and elongate target areas of esophageal cancer.The purpose of this study is to investigate using constant dose rate IMAT on conventional linear accelerator, by comparing with the IMRT technology to evaluate the performance of IMAT on early-stage glottic carcinoma patients and then provide guidance for clinical treatment. The results show that glottic carcinoma can be implemented IMAT plans on conventional Linac for smoothly and quickly at busy cancer center. IMAT planning can meet the clinical demand, showed significant dosimetric benefits in sparing both the thyroid gland and carotid artery. Compared with IMRT, IMAT plan has more MUs and less treatment time and significantly improves the treatment efficiency.An evaluation of weight loss must be performed during treatment for IMAT patients.",
"__typename": "ArticleAbstractType"
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],
"normalizedAbstract": "Previous advanced radiation therapy (RT) techniques for early stage glottic cancer attempted to spare the normal tissue. We aimed to evaluate the dosimetric advantages of intensity modulated arc therapy (IMAT) in terms of increase target tumor dose and sparing normal tissue hand-dose in early-stage glottic cancer patients. In our previous published paper, we explored the application of conventional linear accelerator IMAT technology in large-scale tumors of cervical cancer and elongate target areas of esophageal cancer.The purpose of this study is to investigate using constant dose rate IMAT on conventional linear accelerator, by comparing with the IMRT technology to evaluate the performance of IMAT on early-stage glottic carcinoma patients and then provide guidance for clinical treatment. The results show that glottic carcinoma can be implemented IMAT plans on conventional Linac for smoothly and quickly at busy cancer center. IMAT planning can meet the clinical demand, showed significant dosimetric benefits in sparing both the thyroid gland and carotid artery. Compared with IMRT, IMAT plan has more MUs and less treatment time and significantly improves the treatment efficiency.An evaluation of weight loss must be performed during treatment for IMAT patients.",
"fno": "774400a217",
"keywords": [
"Biological Organs",
"Blood Vessels",
"Cancer",
"Dosimetry",
"Intensity Modulation",
"Linear Accelerators",
"Radiation Therapy",
"Tumours",
"Conventional Linac",
"Dosimetric Advantages",
"Early Stage Glottic Cancer Patients",
"Conventional Linear Accelerator IMAT Technology",
"Large Scale Tumors",
"Cervical Cancer",
"Elongate Target Areas",
"Esophageal Cancer",
"Constant Dose Rate IMAT",
"IMRT Technology",
"Early Stage Glottic Carcinoma Patients",
"Clinical Treatment",
"IMAT Planning",
"Treatment Time",
"IMAT Patients",
"Intensity Modulated Arc Therapy",
"Advanced Radiation Therapy Techniques",
"Treatment Planning",
"Target Tumor Dose",
"Normal Tissue Hand Dose",
"Glottic Carcinoma",
"Thyroid Gland",
"Carotid Artery",
"Planning",
"Medical Treatment",
"Tumors",
"Glands",
"Cervical Cancer",
"Linear Particle Accelerator",
"Glottic Cancer",
"Radiotherapy",
"IMAT",
"IMRT",
"Dosimetry"
],
"authors": [
{
"affiliation": "Dept. of Radiat. Therapy, Fourth Hosp. of Hebei Med. Univ., Shijiazhuang, China",
"fullName": "W.W. Bai",
"givenName": "W.W.",
"surname": "Bai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Radiat. Therapy, Fourth Hosp. of Hebei Med. Univ., Shijiazhuang, China",
"fullName": "Z F. Chi",
"givenName": "Z F.",
"surname": "Chi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Gastroenterology, Hebei Gen. Hosp., Shijiazhuang, China",
"fullName": "Y.L. Gao",
"givenName": "Y.L.",
"surname": "Gao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Radiat. Therapy, Fourth Hosp. of Hebei Med. Univ., Shijiazhuang, China",
"fullName": "Z.H. Jing",
"givenName": "Z.H.",
"surname": "Jing",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Radiat. Therapy, Fourth Hosp. of Hebei Med. Univ., Shijiazhuang, China",
"fullName": "M.C. Miao",
"givenName": "M.C.",
"surname": "Miao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Radiat. Therapy, Fourth Hosp. of Hebei Med. Univ., Shijiazhuang, China",
"fullName": "S G. Wang",
"givenName": "S G.",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Radiat. Therapy, Fourth Hosp. of Hebei Med. Univ., Shijiazhuang, China",
"fullName": "R.H. Zhang",
"givenName": "R.H.",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
}
],
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"pubDate": "2018-10-01T00:00:00",
"pubType": "proceedings",
"pages": "217-220",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-7744-5",
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"id": "1CAThh2drSE",
"title": "2021 11th International Conference on Information Technology in Medicine and Education (ITME)",
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"article": {
"id": "1CATshHvh2E",
"doi": "10.1109/ITME53901.2021.00095",
"title": "TraditionalChineseMedicine characteristic therapy treats obstinate hiccup",
"normalizedTitle": "TraditionalChineseMedicine characteristic therapy treats obstinate hiccup",
"abstract": "Objective: To summarize the curative effect of TCM characteristic therapy on intractable hiccup. Methods: The literature database of TCM characteristic therapy for intractable hiccup was searched and classified, including traditional Chinese medicine, moxibustion therapy, cupping, bloodletting therapy, ear point bean pressing and other treatment methods. Results: The characteristic therapy of Traditional Chinese medicine, moxibustion therapy, cupping therapy, bloodletting therapy, ear point pressing bean treatment of intractable hiccup can relieve the symptoms of hiccup alone or combined, combined application can shorten the disease, reduce the patient's pain and treatment cost. Conclusion: TCM characteristic therapy is effective in treating intractable hiccup, with rapid symptom relief and low recurrence rate. Comprehensive application is better than single application.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Objective: To summarize the curative effect of TCM characteristic therapy on intractable hiccup. Methods: The literature database of TCM characteristic therapy for intractable hiccup was searched and classified, including traditional Chinese medicine, moxibustion therapy, cupping, bloodletting therapy, ear point bean pressing and other treatment methods. Results: The characteristic therapy of Traditional Chinese medicine, moxibustion therapy, cupping therapy, bloodletting therapy, ear point pressing bean treatment of intractable hiccup can relieve the symptoms of hiccup alone or combined, combined application can shorten the disease, reduce the patient's pain and treatment cost. Conclusion: TCM characteristic therapy is effective in treating intractable hiccup, with rapid symptom relief and low recurrence rate. Comprehensive application is better than single application.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Objective: To summarize the curative effect of TCM characteristic therapy on intractable hiccup. Methods: The literature database of TCM characteristic therapy for intractable hiccup was searched and classified, including traditional Chinese medicine, moxibustion therapy, cupping, bloodletting therapy, ear point bean pressing and other treatment methods. Results: The characteristic therapy of Traditional Chinese medicine, moxibustion therapy, cupping therapy, bloodletting therapy, ear point pressing bean treatment of intractable hiccup can relieve the symptoms of hiccup alone or combined, combined application can shorten the disease, reduce the patient's pain and treatment cost. Conclusion: TCM characteristic therapy is effective in treating intractable hiccup, with rapid symptom relief and low recurrence rate. Comprehensive application is better than single application.",
"fno": "067900a446",
"keywords": [
"Data Mining",
"Diseases",
"Drug Delivery Systems",
"Medical Disorders",
"Regression Analysis",
"Obstinate Hiccup",
"TCM Characteristic Therapy",
"Intractable Hiccup",
"Moxibustion Therapy",
"Ear Point Bean Pressing",
"Traditional Chinese Medicine Characteristic Therapy",
"Costs",
"Pain",
"Databases",
"Education",
"Medical Treatment",
"Pressing",
"Ear",
"Hiccup",
"TCM Characteristic Therapy",
"Moxibustion Therapy",
"Summary"
],
"authors": [
{
"affiliation": "Hebei Academy of Traditional Chinese Medicine,Shijiazhuang,China",
"fullName": "Shengda Lu",
"givenName": "Shengda",
"surname": "Lu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hebei Academy of Traditional Chinese Medicine,Shijiazhuang,China",
"fullName": "Xiaofa Liu",
"givenName": "Xiaofa",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The second affiliated Hospital of Xingtai Medical College,Xingtai,China",
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"givenName": "Ruiyu",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hebei Academy of Traditional Chinese Medicine,Shijiazhuang,China",
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"givenName": "Sujie",
"surname": "Jia",
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{
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"year": "2020",
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"id": "1qmg4AVFi80",
"doi": "10.1109/BIBM49941.2020.9313509",
"title": "A multi-task learning method for analyzing microbiota as cancer immunotherapy signal",
"normalizedTitle": "A multi-task learning method for analyzing microbiota as cancer immunotherapy signal",
"abstract": "Researches have found that tumor immunotherapy can only work for some patients, and the intestinal microbiota is one of the important factors affecting the responses of patients with cancer to immune checkpoint blockade therapy. It is highly desirable to develop computational methods that can predict whether a patient with cancer will have positive effects on cancer immunotherapy by analyzing intestinal microorganisms of the patient. In this study, a multi-task model is introduced to predict the efficacy of cancer immunotherapy on a patient who suffered from non-small cell lung cancer or renal cell carcinoma. The results demonstrate the multi-task model outperforms several single-task methods. Therefore, we believe the multi-task idea can be used to predict the efficacy of cancer immunotherapy based on the gut microbe, which would be important to cancer patients.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Researches have found that tumor immunotherapy can only work for some patients, and the intestinal microbiota is one of the important factors affecting the responses of patients with cancer to immune checkpoint blockade therapy. It is highly desirable to develop computational methods that can predict whether a patient with cancer will have positive effects on cancer immunotherapy by analyzing intestinal microorganisms of the patient. In this study, a multi-task model is introduced to predict the efficacy of cancer immunotherapy on a patient who suffered from non-small cell lung cancer or renal cell carcinoma. The results demonstrate the multi-task model outperforms several single-task methods. Therefore, we believe the multi-task idea can be used to predict the efficacy of cancer immunotherapy based on the gut microbe, which would be important to cancer patients.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Researches have found that tumor immunotherapy can only work for some patients, and the intestinal microbiota is one of the important factors affecting the responses of patients with cancer to immune checkpoint blockade therapy. It is highly desirable to develop computational methods that can predict whether a patient with cancer will have positive effects on cancer immunotherapy by analyzing intestinal microorganisms of the patient. In this study, a multi-task model is introduced to predict the efficacy of cancer immunotherapy on a patient who suffered from non-small cell lung cancer or renal cell carcinoma. The results demonstrate the multi-task model outperforms several single-task methods. Therefore, we believe the multi-task idea can be used to predict the efficacy of cancer immunotherapy based on the gut microbe, which would be important to cancer patients.",
"fno": "09313509",
"keywords": [
"Cancer",
"Cellular Biophysics",
"Kidney",
"Learning Artificial Intelligence",
"Lung",
"Medical Computing",
"Microorganisms",
"Patient Treatment",
"Tumours",
"Multitask Learning Method",
"Cancer Immunotherapy Signal",
"Tumor Immunotherapy",
"Intestinal Microbiota",
"Immune Checkpoint Blockade Therapy",
"Computational Methods",
"Nonsmall Cell Lung Cancer",
"Single Task Methods",
"Renal Cell Carcinoma",
"Task Analysis",
"Immune System",
"Cancer",
"Tumors",
"Medical Treatment",
"Support Vector Machines",
"Predictive Models",
"Multi Task Model",
"Cancer Immunotherapy",
"Gut Microbe"
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"authors": [
{
"affiliation": "Xiamen University,Department of Computer Science,Xiamen,China",
"fullName": "Changzhi Jiang",
"givenName": "Changzhi",
"surname": "Jiang",
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{
"affiliation": "Xiamen University,School of Life Sciences,Xiamen,China",
"fullName": "Yousi Fu",
"givenName": "Yousi",
"surname": "Fu",
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{
"affiliation": "Xiamen University,Department of Computer Science,Xiamen,China",
"fullName": "Shuting Jin",
"givenName": "Shuting",
"surname": "Jin",
"__typename": "ArticleAuthorType"
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"abstract": "Modeling disease relationships and temporal progression are two key problems in health analytics, which have not been studied together due to data and technical challenges. Thanks to the increasing adoption of Electronic Health Records (EHR), rich patient information is being collected over time. Using EHR data as input, we propose a multivariate context-sensitive Hawkes process or cHawkes, which simultaneously infers the disease relationship network and models temporal progression of patients. Besides learning disease network and temporal progression model, cHawkes is able to predict when a specific patient might have other related diseases in future given the patient history, which in turn can have many potential applications in predictive health analytics, public health policy development and customized patient care. Extensive experiments on real EHR data demonstrate that cHawkes not only can uncover meaningful disease relations and model accurate temporal progression of patients, but also has significantly better predictive performance compared to several baseline models.",
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"content": "Amyotrophic Lateral Sclerosis (ALS) is a neurode-generative disease highly known for its rapid progression, leading to death usually within a few years. Respiratory failure is the most common cause of death. Therefore, efforts must be taken to prevent respiratory insufficiency. Preventive administration of non-invasive ventilation (NIV) has proven to improve survival in ALS patients. Using disease progression groups revealed to be of great importance to ALS studies, since the heterogeneous nature of disease presentation and progression presents challenges to the learn of predictive models that work for all patients. In this context, we propose an approach to stratify patients in three progression groups (Slow, Neutral and Fast) enabling the creation of specialized learning models that predict the need of NIV within a time window of 90, 180 or 365 days of their current medical appointment. The models are built using a collection of classifiers and 5x10-fold cross validation. We also test the use of a Feature Selection Ensemble to test which features are more relevant to predict this outcome. Our specialized predictive models showed promising results, proving the utility of patient stratification when predicting NIV in ALS patients.",
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"normalizedAbstract": "Amyotrophic Lateral Sclerosis (ALS) is a neurode-generative disease highly known for its rapid progression, leading to death usually within a few years. Respiratory failure is the most common cause of death. Therefore, efforts must be taken to prevent respiratory insufficiency. Preventive administration of non-invasive ventilation (NIV) has proven to improve survival in ALS patients. Using disease progression groups revealed to be of great importance to ALS studies, since the heterogeneous nature of disease presentation and progression presents challenges to the learn of predictive models that work for all patients. In this context, we propose an approach to stratify patients in three progression groups (Slow, Neutral and Fast) enabling the creation of specialized learning models that predict the need of NIV within a time window of 90, 180 or 365 days of their current medical appointment. The models are built using a collection of classifiers and 5x10-fold cross validation. We also test the use of a Feature Selection Ensemble to test which features are more relevant to predict this outcome. Our specialized predictive models showed promising results, proving the utility of patient stratification when predicting NIV in ALS patients.",
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"abstract": "Disease progression modeling (DPM) involves using mathematical frameworks to quantitatively measure the severity of how certain disease progresses. DPM is useful in many ways such as predicting health state, categorizing disease stages, and assessing patients’ disease trajectory, etc. Recently, with the wider availability of electronic health records (EHR) and the broad application of data-driven machine learning methods, DPM has attracted much attention yet remains two major challenges: (i) Due to the existence of irregularity, heterogeneity, and long-term dependency in EHRs, most existing DPM methods might not be able to provide comprehensive patient representations. (ii) Lots of records in EHRs might be irrelevant to the target disease. Most existing models learn to automatically focus on the relevant information instead of explicitly capture the target-relevant events, which might make the learned model suboptimal. To address these two issues, we propose Temporal Clustering with External Memory Network (TC-EMNet) for DPM that groups patients with similar trajectories to form disease clusters/stages. TC-EMNet uses a variational autoencoder (VAE) to capture internal complexity from the input data and utilizes an external memory work to capture long-term distance information, both of which are helpful for producing comprehensive patient health states. Last but not least, the k-means algorithm is adopted to cluster the extracted comprehensive patient representation to capture disease progression. Experiments on two real-world datasets show that our model demonstrates competitive clustering performance against state-of-the-art methods and is able to identify clinically meaningful clusters. The visualization of the patient representations shows that the proposed model can generate better patient health states than the baselines.",
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"content": "Disease progression modeling (DPM) involves using mathematical frameworks to quantitatively measure the severity of how certain disease progresses. DPM is useful in many ways such as predicting health state, categorizing disease stages, and assessing patients’ disease trajectory, etc. Recently, with the wider availability of electronic health records (EHR) and the broad application of data-driven machine learning methods, DPM has attracted much attention yet remains two major challenges: (i) Due to the existence of irregularity, heterogeneity, and long-term dependency in EHRs, most existing DPM methods might not be able to provide comprehensive patient representations. (ii) Lots of records in EHRs might be irrelevant to the target disease. Most existing models learn to automatically focus on the relevant information instead of explicitly capture the target-relevant events, which might make the learned model suboptimal. To address these two issues, we propose Temporal Clustering with External Memory Network (TC-EMNet) for DPM that groups patients with similar trajectories to form disease clusters/stages. TC-EMNet uses a variational autoencoder (VAE) to capture internal complexity from the input data and utilizes an external memory work to capture long-term distance information, both of which are helpful for producing comprehensive patient health states. Last but not least, the k-means algorithm is adopted to cluster the extracted comprehensive patient representation to capture disease progression. Experiments on two real-world datasets show that our model demonstrates competitive clustering performance against state-of-the-art methods and is able to identify clinically meaningful clusters. The visualization of the patient representations shows that the proposed model can generate better patient health states than the baselines.",
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"affiliation": "The Ohio State University,Department of Computer Science and Engineering,Columbus,USA",
"fullName": "Zicong Zhang",
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"abstract": "Patient journeys are the key for treatment development, quality insurance and better understanding of disease progression. Therefore, many visualization toolkits exist to monitor individual patient lives. However, there is no visualization that relies on the overall patterns of patient journeys. We propose a new framework progViz that visualizes patterns of patient journeys, which rely on finite state models. These models are able to illustrate progression of diseases, treatment and outcomes of whole populations as well as very specific analyses. Finally, we propose a method to evaluate how treatment affects disease progression.",
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"affiliation": "Institute of Informatics, LMU Munich",
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"abstract": "Modeling patient disease progression using their historical Electronic Health Records (EHRs) is critical to assist clinical decision making and provide prompt medications. Long-Short Term Memory (LSTM) has been widely applied to handle large-scale sequential data such as EHRs. However, when applied to EHRs, the standard LSTM encounters one major limitation: lack of the generalizability given the intricate heterogeneity among different patient groups. To overcome this limitation, we propose a domain adaptation (DA) framework named Time-aware Adversarial Networks, which combines two temporal LSTM-based recurrent components, a label predictor and a domain classifier, to extract an invariant feature representation across different patient groups (domains) through an adversarial learning process. The label predictor learns the temporal developing patterns of the disease while the domain classifier identifies the temporal changes of feature distributions across patient groups. We evaluate the proposed DA framework on modeling the progression of an extremely challenging disease, septic shock, by using real-world EHRs among different patient groups across age, race, and gender. Our results demonstrate that our proposed DA framework can significantly improve the performance for the disease progression modeling while standard machine learning models are severely impacted by the data heterogeneity in EHRs.",
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"abstract": "Parkinson's Disease (PD) is the second most common neurodegenerative disease in the United States, and is characterized by the progressive decline of motor and non-motor symptoms. The progression rate and manifestation of PD is highly heterogenous, and the underlying etiology for this heterogeneity remains elusive. Although some studies have identified risk genes associated with the development of PD, it is unknown whether the patient genome influences the progression pattern of PD in any way. In this study, we used the whole-exome sequencing data of PD patients from the Parkinson's Disease Progression Marker Initiative (PPMI) to examine whether an individual's genetic profile is associated with their progression pattern of PD. We used the three distinct progression subtypes defined by Zhang et al. as the outcome variable, and trained logistic regression and support vector classifiers. Our best performing model achieved an area under the receiver operating characteristic curve of 0.69 on the test set, indicating that the genetic profile of a PD patient appears to have some relationship with their likely disease course. We then interpreted our trained model by performing Gene Set Enrichment Analysis on the sets of genes with high model coefficients for each progression subtype. The results showed enrichment for genes related to olfactory signaling in Subtype I and III, and an enrichment for genes related to protein glycosylation and glycation for Subtype I and II. Overall, our findings suggests a connection between an individual's genetic profile and PD progression subtype, and calls for controlled research studies to further examine the relationship between the implicated gene sets and each progression subtype.",
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"content": "Parkinson's Disease (PD) is the second most common neurodegenerative disease in the United States, and is characterized by the progressive decline of motor and non-motor symptoms. The progression rate and manifestation of PD is highly heterogenous, and the underlying etiology for this heterogeneity remains elusive. Although some studies have identified risk genes associated with the development of PD, it is unknown whether the patient genome influences the progression pattern of PD in any way. In this study, we used the whole-exome sequencing data of PD patients from the Parkinson's Disease Progression Marker Initiative (PPMI) to examine whether an individual's genetic profile is associated with their progression pattern of PD. We used the three distinct progression subtypes defined by Zhang et al. as the outcome variable, and trained logistic regression and support vector classifiers. Our best performing model achieved an area under the receiver operating characteristic curve of 0.69 on the test set, indicating that the genetic profile of a PD patient appears to have some relationship with their likely disease course. We then interpreted our trained model by performing Gene Set Enrichment Analysis on the sets of genes with high model coefficients for each progression subtype. The results showed enrichment for genes related to olfactory signaling in Subtype I and III, and an enrichment for genes related to protein glycosylation and glycation for Subtype I and II. Overall, our findings suggests a connection between an individual's genetic profile and PD progression subtype, and calls for controlled research studies to further examine the relationship between the implicated gene sets and each progression subtype.",
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"normalizedAbstract": "Parkinson's Disease (PD) is the second most common neurodegenerative disease in the United States, and is characterized by the progressive decline of motor and non-motor symptoms. The progression rate and manifestation of PD is highly heterogenous, and the underlying etiology for this heterogeneity remains elusive. Although some studies have identified risk genes associated with the development of PD, it is unknown whether the patient genome influences the progression pattern of PD in any way. In this study, we used the whole-exome sequencing data of PD patients from the Parkinson's Disease Progression Marker Initiative (PPMI) to examine whether an individual's genetic profile is associated with their progression pattern of PD. We used the three distinct progression subtypes defined by Zhang et al. as the outcome variable, and trained logistic regression and support vector classifiers. Our best performing model achieved an area under the receiver operating characteristic curve of 0.69 on the test set, indicating that the genetic profile of a PD patient appears to have some relationship with their likely disease course. We then interpreted our trained model by performing Gene Set Enrichment Analysis on the sets of genes with high model coefficients for each progression subtype. The results showed enrichment for genes related to olfactory signaling in Subtype I and III, and an enrichment for genes related to protein glycosylation and glycation for Subtype I and II. Overall, our findings suggests a connection between an individual's genetic profile and PD progression subtype, and calls for controlled research studies to further examine the relationship between the implicated gene sets and each progression subtype.",
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"affiliation": "Northwestern University,Department of Preventive Medicine,Chicago,USA",
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"abstract": "Phase Contrast (PC) and Differential Interference Contrast (DIC) microscopy are two popular non-invasive techniques for monitoring live cells. Each of these two image modalities has its own advantages and disadvantages to visualize specimens, so biologists need these two complementary modalities together to analyze specimens. In this paper, we investigate a conditional Generative Adversarial Network (conditional GAN), which contains one generator and two discriminators, to transfer microscopy image modalities. Given a training dataset consisting of pairs of images (source and destination) captured on the same set of specimens by DIC and Phase Contrast microscopes, we can train a conditional GAN, and with this well-trained GAN, we can generate the corresponding Phase Contrast image given a new DIC image, vice versa. The preliminary experiments demonstrate that our approach outperforms one state-of-the-arts method, and can provide biologists a computational way to switch between microscopy image modalities, so biologists can combine the advantages of different image modalities to better visualize and analyze specimens over time, without purchasing all types of microscopy image modalities or switching between imaging systems back-andforth during time-lapse experiments.",
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"content": "Phase Contrast (PC) and Differential Interference Contrast (DIC) microscopy are two popular non-invasive techniques for monitoring live cells. Each of these two image modalities has its own advantages and disadvantages to visualize specimens, so biologists need these two complementary modalities together to analyze specimens. In this paper, we investigate a conditional Generative Adversarial Network (conditional GAN), which contains one generator and two discriminators, to transfer microscopy image modalities. Given a training dataset consisting of pairs of images (source and destination) captured on the same set of specimens by DIC and Phase Contrast microscopes, we can train a conditional GAN, and with this well-trained GAN, we can generate the corresponding Phase Contrast image given a new DIC image, vice versa. The preliminary experiments demonstrate that our approach outperforms one state-of-the-arts method, and can provide biologists a computational way to switch between microscopy image modalities, so biologists can combine the advantages of different image modalities to better visualize and analyze specimens over time, without purchasing all types of microscopy image modalities or switching between imaging systems back-andforth during time-lapse experiments.",
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