基於模糊邏輯和領域本體之以病患為中心的糖尿病治療決策支持系統

A Patient-Centered Treatment Decision Support System for Diabetes Based on Fuzzy Logic and Domain Ontology

黃忠義(Chung-Yi Huang)

指導教授 ： 陳隆昇 ； 陳榮靜

朝陽科技大學/資訊學院/資訊管理系/博士(2017年)

摘要

糖尿病患者的數量愈來愈多，且糖尿病不僅對患者造成心理和身體疼痛外，而且還具有很高的醫療成本。由於第二型糖尿病患者的表現型差異性很大，因此導致臨床結果出現明顯的異質性。故臨床醫生在開立的處方策略時，必須考慮很多因素，以選擇出最適合患者的需求。
本論文提出以病患為中心的糖尿病治療決策支持系統，並開發出一套抗糖尿病藥物推薦系統。我們採用美國糖尿病協會（ADA）和歐洲糖尿病研究協會（EASD）聯合發表關於第二型糖尿病患者高血糖管理的聲明，建立HbA1c目標推理模型和藥物知識本體，並結合模糊邏輯和本體推理技術建立了針對T2DM患者的抗糖尿病藥物推薦系統。此外，為了將推薦出來的糖尿病藥物進行推薦排序，再以美國臨床內分泌學家協會（AACE）和美國內分泌學會（ACE）發表的血糖控制算法，結合TOPSIS技術來計算藥物與理想解答的相對接近度，以評估抗糖尿病藥物的推薦優先順序。
本系統透過糖尿病專科醫師創建的十個虛擬病人的醫療數據，來評估決策支持系統。評估結果表明本研究設計的臨床決策支援系統(CDSS)適用於門診病人，其有用性評估結果為87％。另依抗糖尿病藥物推薦的評價結果，本系統具有85％的滿意度，且參與的臨床醫生有77％的信心接受在工作中使用本系統，並將其推薦給其他人。本系統除了推薦適用於患者的抗糖尿病藥物給臨床醫生外，並針對患者的個人化狀況對推薦藥物進行優先順序評估，因此未來可以輔助非專科醫生和年輕醫生在開立糖尿病處方藥物時，作為參考資訊。

關鍵字

以患者為中心的決策 ； 模糊系統 ； 第2型糖尿病 ； 領域本體 ； 臨床決策支持系統

並列摘要

The number of patients with diabetes is both large and increasing. Diabetes not only imposes psychological and physical pain on patients but also has high medical costs. Thus, the prescription strategy of clinical doctors must consider many factors, because patients with Type 2 diabetes mellitus exhibit tremendous differences in phenotypes, resulting in significant heterogeneity in clinical results.
In this thesis, we create a patient-centered treatment decision support system for diabetes and develop an antidiabetic medications recommendation system. We adopted the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) published an update of the position statement on management of Hyperglycemia in Type 2 diabetes to build HbA1c target inference module and the drug knowledge ontology. The system combines fuzzy logics and ontology reasoning to propose an antidiabetic medications recommendation system for patients with T2DM. Based on the American Association of Clinical Endocrinologists (AACE) and the American College of Endocrinology (ACE) published algorithm for glycemic control, we used Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to calculate the relative closeness to the ideal solution and then determined ranking of antidiabetic medications.
The endocrinologist created ten virtual patients’ medical data to evaluate a decision support system. The system indicated that the Clinical Decision Support System (CDSS) performed well and was useful in 87% of cases studied, and the recommendation system is suitable for outpatients. The evaluation results of the antidiabetic medications recommendation show that the system has 85% satisfaction degree which can assist clinicians to management T2DM while selecting antidiabetic medications. The participating clinicians have 77% acceptance of enjoy using this system at work and will recommend it to other clinicians. In addition to aiding doctors’ clinical diagnosis, the system not only can serve as a guide for doctors specializing in diabetes but also can help family doctors and doctors in internships in prescribing antidiabetic medications.

並列關鍵字

Patient-centered decision making ； Fuzzy system ； Type 2 diabetes ； Domain ontology ； Clinical decision support system

參考文獻

1. International Diabetes Federation (IDF) (2015), IDF Diabetes Atlas, Seventh Edition: International Diabetes Federation. Brussels, Belgium.

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7. S. E. Inzucchi, R. M. Bergenstal, J. B. Buse, M. Diamant, E. Ferrannini, M. Nauck, et al. (2012), "Management of Hyperglycemia in Type 2 Diabetes: A Patient-Centered Approach: Position Statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)," Diabetes Care, Vol. 35, No. 6, pp. 1364-1379.

8. S. E. Inzucchi, R. M. Bergenstal, J. B. Buse, M. Diamant, E. Ferrannini, M. Nauck, et al. (2015), "Management of Hyperglycemia in Type 2 Diabetes, 2015: A Patient-Centered Approach: Update to a Position Statement of the American Diabetes Association and the European Association for the Study of Diabetes," Diabetes Care, Vol. 38, No. 1, pp. 140-149.