Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis
Joint Authors
Bau, Cho-Tsan
Jiang, Hui Qin
Huang, Chung-Yi
Chen, Rung-Ching
Source
Journal of Healthcare Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-26
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Introduction.
Although a number of researchers have considered the positive potential of Clinical Decision Support System (CDSS), they did not consider that patients’ attitude which leads to active treatment strategies or HbA1c targets.
Materials and Methods.
We adopted the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) published to propose an HbA1c target and antidiabetic medication recommendation system for patients.
Based on the antidiabetic medication profiles, which were presented by the American Association of Clinical Endocrinologists (AACE) and American College of Endocrinology (ACE), we use TOPSIS to calculate the ranking of antidiabetic medications.
Results.
The endocrinologist set up ten virtual patients’ medical data to evaluate a decision support system.
The system indicates that the CDSS performs well and is useful to 87%, and the recommendation system is suitable for outpatients.
The evaluation results of the antidiabetic medications show that the system has 85% satisfaction degree which can assist clinicians to manage T2DM while selecting antidiabetic medications.
Conclusions.
In addition to aiding doctors’ clinical diagnosis, the system not only can serve as a guide for specialty physicians but also can help nonspecialty doctors and young doctors with their drug prescriptions.
American Psychological Association (APA)
Chen, Rung-Ching& Jiang, Hui Qin& Huang, Chung-Yi& Bau, Cho-Tsan. 2017. Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1180974
Modern Language Association (MLA)
Chen, Rung-Ching…[et al.]. Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis. Journal of Healthcare Engineering No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1180974
American Medical Association (AMA)
Chen, Rung-Ching& Jiang, Hui Qin& Huang, Chung-Yi& Bau, Cho-Tsan. Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1180974
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1180974