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Your search keyword '"Jian, Wen-Shan"' showing total 298 results
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298 results on '"Jian, Wen-Shan"'

1. Misleading Health-Related Information Promoted Through Video-Based Social Media: Anorexia on YouTube

Author

Syed-Abdul, Shabbir, Fernandez-Luque, Luis, Jian, Wen-Shan, Li, Yu-Chuan, Crain, Steven, Hsu, Min-Huei, Wang, Yao-Chin, Khandregzen, Dorjsuren, Chuluunbaatar, Enkhzaya, Nguyen, Phung Anh, and Liou, Der-Ming

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

IntroductionThe amount of information being uploaded onto social video platforms, such as YouTube, Vimeo, and Veoh, continues to spiral, making it increasingly difficult to discern reliable health information from misleading content. There are thousands of YouTube videos promoting misleading information about anorexia (eg, anorexia as a healthy lifestyle). ObjectiveThe aim of this study was to investigate anorexia-related misinformation disseminated through YouTube videos. MethodsWe retrieved YouTube videos related to anorexia using the keywords anorexia, anorexia nervosa, proana, and thinspo on October 10, 2011.Three doctors reviewed 140 videos with approximately 11 hours of video content, classifying them as informative, pro-anorexia, or others. By informative we mean content describing the health consequences of anorexia and advice on how to recover from it; by pro-anorexia we mean videos promoting anorexia as a fashion, a source of beauty, and that share tips and methods for becoming and remaining anorexic. The 40 most-viewed videos (20 informative and 20 pro-anorexia videos) were assessed to gauge viewer behavior. ResultsThe interrater agreement of classification was moderate (Fleiss’ kappa=0.5), with 29.3% (n=41) being rated as pro-anorexia, 55.7% (n=78) as informative, and 15.0% (n=21) as others. Pro-anorexia videos were favored 3 times more than informative videos (odds ratio [OR] 3.3, 95% CI 3.3-3.4, P

Published
2013
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7. A richly interactive exploratory data analysis and visualization tool using electronic medical records

Author

Huang, Chih-Wei, Lu, Richard, Iqbal, Usman, Lin, Shen-Hsien, Nguyen, Phung Anh Alex, Yang, Hsuan-Chia, Wang, Chun-Fu, Li, Jianping, Ma, Kwan-Liu, Li, Yu-Chuan Jack, and Jian, Wen-Shan

Subjects
Networking and Information Technology R&D (NITRD), Clinical Research, Bioengineering, Generic health relevance, Clinical Studies as Topic, Data Interpretation, Statistical, Electronic Health Records, Humans, Information Storage and Retrieval, National Health Programs, Pilot Projects, Taiwan, Information Systems, Clinical Sciences, Medical Informatics
Abstract

BackgroundElectronic medical records (EMRs) contain vast amounts of data that is of great interest to physicians, clinical researchers, and medial policy makers. As the size, complexity, and accessibility of EMRs grow, the ability to extract meaningful information from them has become an increasingly important problem to solve.MethodsWe develop a standardized data analysis process to support cohort study with a focus on a particular disease. We use an interactive divide-and-conquer approach to classify patients into relatively uniform within each group. It is a repetitive process enabling the user to divide the data into homogeneous subsets that can be visually examined, compared, and refined. The final visualization was driven by the transformed data, and user feedback direct to the corresponding operators which completed the repetitive process. The output results are shown in a Sankey diagram-style timeline, which is a particular kind of flow diagram for showing factors' states and transitions over time.ResultsThis paper presented a visually rich, interactive web-based application, which could enable researchers to study any cohorts over time by using EMR data. The resulting visualizations help uncover hidden information in the data, compare differences between patient groups, determine critical factors that influence a particular disease, and help direct further analyses. We introduced and demonstrated this tool by using EMRs of 14,567 Chronic Kidney Disease (CKD) patients.ConclusionsWe developed a visual mining system to support exploratory data analysis of multi-dimensional categorical EMR data. By using CKD as a model of disease, it was assembled by automated correlational analysis and human-curated visual evaluation. The visualization methods such as Sankey diagram can reveal useful knowledge about the particular disease cohort and the trajectories of the disease over time.

Published
2015

9. A novel tool for visualizing chronic kidney disease associated polymorbidity: a 13-year cohort study in Taiwan

Author

Huang, Chih-Wei, Syed-Abdul, Shabbir, Jian, Wen-Shan, Iqbal, Usman, Nguyen, Phung-Anh, Lee, Peisan, Lin, Shen-Hsien, Hsu, Wen-Ding, Wu, Mai-Szu, Wang, Chun-Fu, Ma, Kwan-Liu, and Li, Yu-Chuan

Subjects
Kidney Disease, Renal and urogenital, Audiovisual Aids, Cohort Studies, Comorbidity, Data Display, Disease Progression, Humans, Pattern Recognition, Automated, Pilot Projects, Renal Insufficiency, Chronic, Taiwan, Time Factors, User-Computer Interface, visualize analytic, data visualization, CKD polymorbidity visualization, comorbidity visualization, CKD Sankey diagram, Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics
Abstract

ObjectiveThe aim of this study is to analyze and visualize the polymorbidity associated with chronic kidney disease (CKD). The study shows diseases associated with CKD before and after CKD diagnosis in a time-evolutionary type visualization.Materials and methodsOur sample data came from a population of one million individuals randomly selected from the Taiwan National Health Insurance Database, 1998 to 2011. From this group, those patients diagnosed with CKD were included in the analysis. We selected 11 of the most common diseases associated with CKD before its diagnosis and followed them until their death or up to 2011. We used a Sankey-style diagram, which quantifies and visualizes the transition between pre- and post-CKD states with various lines and widths. The line represents groups and the width of a line represents the number of patients transferred from one state to another.ResultsThe patients were grouped according to their states: that is, diagnoses, hemodialysis/transplantation procedures, and events such as death. A Sankey diagram with basic zooming and planning functions was developed that temporally and qualitatively depicts they had amid change of comorbidities occurred in pre- and post-CKD states.DiscussionThis represents a novel visualization approach for temporal patterns of polymorbidities associated with any complex disease and its outcomes. The Sankey diagram is a promising method for visualizing complex diseases and exploring the effect of comorbidities on outcomes in a time-evolution style.ConclusionsThis type of visualization may help clinicians foresee possible outcomes of complex diseases by considering comorbidities that the patients have developed.

Published
2015

17. Cloud-based BP system integrated with CPOE improves self-management of the hypertensive patients: A randomized controlled trial

Author

Lee, Peisan, Liu, Ju-Chi, Hsieh, Ming-Hsiung, Hao, Wen-Rui, Tseng, Yuan-Teng, Liu, Shuen-Hsin, Lin, Yung-Kuo, Sung, Li-Chin, Huang, Jen-Hung, Yang, Hung-Yu, Ye, Jong-Shiuan, Zheng, He-Shun, Hsu, Min-Huei, Syed-Abdul, Shabbir, Lu, Richard, Nguyen, Phung-Anh, Iqbal, Usman, Huang, Chih-Wei, Jian, Wen-Shan, and Li, Yu-Chuan (Jack)

Published
2016
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42. Correlation Between Previous Caesarean Section and Adverse Maternal Outcomes Accordingly With Robson Classification: Systematic Review and Meta-Analysis

Author

Jamshed, Shazia, primary, Chien, Shuo-Chen, additional, Tanweer, Afifa, additional, Asdary, Rahma-Novita, additional, Hardhantyo, Muhammad, additional, Greenfield, David, additional, Chien, Chia-Hui, additional, Weng, Shuen-Fu, additional, Jian, Wen-Shan, additional, and Iqbal, Usman, additional

Published
2022
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50. A novel method to retrieve alerts from a homegrown Computerized Physician Order Entry (CPOE) system of an academic medical center: Comprehensive alert characteristic analysis

Author

Chien, Shuo-Chen, primary, Chin, Yen-Po (Harvey), additional, Yoon, Chang Ho, additional, Islam, Md. Mohaimenul, additional, Jian, Wen-Shan, additional, Hsu, Chun-Kung, additional, Chen, Chun-You, additional, Chien, Po-Han, additional, and Li, Yu-Chuan (Jack), additional

Published
2021
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