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

Public Health
Medicine

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