跳到主要內容

臺灣博碩士論文加值系統

(216.73.216.60) 您好!臺灣時間:2026/06/24 00:27
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:廖子婷
研究生(外文):Liao, Zi-Ting
論文名稱:建構智慧型醫療診斷決策支援系統
論文名稱(外文):Developing an Intelligent Decision Support System for Medical Diagnosis
指導教授:張俊陽
指導教授(外文):Chang, Chun-Yang
口試委員:孫培真李慶章張俊陽
口試委員(外文):SUN, PEI-ZHENLI, QING-ZHANGChang, Chun-Yang
口試日期:2018-07-21
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:資訊管理研究所碩士班
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:中文
論文頁數:55
中文關鍵詞:智慧醫療決策支援系統專家系統評估指標
外文關鍵詞:Smart MedicalDecision Support SystemExpert SystemEvaluation Index
相關次數:
  • 被引用被引用:0
  • 點閱點閱:449
  • 評分評分:
  • 下載下載:15
  • 收藏至我的研究室書目清單書目收藏:1
本研究目的為建構一套智慧型醫療診斷決策支援系統。首先,結合過去智慧醫療、決策支援系統、專家系統、案例式推理等文獻提出本研究之系統架構圖,其次,以敏捷式開發法導出系統開發之流程,包括醫師診斷、醫師評估病情、開立處方簽、後續觀察四階段,最後透過資訊系統成功模式提出5個構面,分別為系統品質、資訊品質、服務品質、對個人績效影響、對組織績效影響,並導出24個評估指標,來探討對使用者的效益。

本研究建構的智慧型醫療診斷決策支援系統功能包含:診斷決策支援、用藥劑量決策支援、遠端照護支援等三大功能,幫助醫師提升診斷效率,也提供更多資訊來源做為決策參考,減少誤診,提升醫療品質。此外,經由資訊系統效益評估問卷調查顯示,在系統品質方面:使用者對系統的資料存取的穩定性、實用性、精準性與保密性等項目感到非常滿意;在資訊品質方面:使用者對系統提供的資訊正確性、完整性、有用性、相關性等項目感到非常滿意;在服務品質方面:使用者對資訊人員的親切度感到非常滿意;在個人績效方面,使用者對能有效分析大量資料、減少人工計算時間項目感到非常滿意;在組織績效方面,使用者對能提升組織營運效能感到非常滿意。

The purpose of this study is to develop an intelligent decision support system for medical diagnosis. First, this paper integrates smart health, decision support system, expert system, and case-based reasoning literature to proposed the system architecture diagram of this research, secondly, the process of system development is based on agile development method, the process including physician diagnosis, physician evaluation of the condition, write prescription, and follow-up observation in four stages. Finally, this study presents a total of 24 evaluation index from 5 dimensions, such as system quality, information quality, service quality, impact on individual performance, impact on organizational performance to explore the benefits to users with the system.

The intelligent decision support system for medical diagnosis develop in this study includes three functions: diagnostic decision support, dose decision support, and remote care support. It not only helps doctors improve efficiency in diagnosis, but also provides more information sources as decision-making reference, reduce the situation of misdiagnosis and improve the quality of medical care. In addition, the results of the questionnaire survey shows that homebuyers are satisfied with the system’s convenience, integration, reliability, and ease of use in system quality; information is correctness, reliability, integrity, conciseness, understanding in information quality; intimacy of information personnel in service quality; effective analysis of large amounts of data and reduction of manual calculation time in personal performance; improve organizational operational effectiveness in organizational performance.

摘 要
ABSTRACT
誌 謝
目錄
表目錄
圖目錄
一、 緒論
1.1 研究背景
1.2 研究動機
1.3 研究目的
1.4 論文架構
二、 文獻探討
2.1 智慧型醫療診斷決策支援系統
2.1.1 智慧醫療
2.1.2 決策支援系統
2.1.3 案例式推理
2.1.4 專家系統
2.2 DeLone & McLean(2003)修正後資訊系統成功模式
三、 研究方法
3.1 智慧型醫療診斷決策支援系統
3.2 資訊系統開發方法
3.3 智慧型醫療診斷決策支援系統開發程序
3.3.1 第一階段 : 系統需求規劃
3.3.2 第二階段 : 使用者需求設計
3.3.3 第三階段 : 系統開發雛形建置
3.3.4 第四階段 : 建構與切換
3.3.5 第五階段 : 資訊系統效益評估
四、 研究結果
4.1 案例介紹
4.2 智慧型醫療管理決策支援系統開發結果
4.2.1 第一階段 : 系統需求規劃結果
4.2.2 第二階段 : 使用者需求設計結果
4.2.3 第三階段 : 系統開發雛形建置結果
4.2.4 第四階段 : 建構與切換結果
4.2.5 第五階段 : 資訊系統效益評估結果
五、 結論與建議
5.1 學術貢獻
5.2 實務貢獻
5.3 管理意涵
5.4 研究限制
5.5 未來研究與建議
參考文獻
附錄:智慧型醫療診斷決策支援系統使用效益之調查問卷

1.李炫昇,楊雪芳,2014,“住院照護行動醫療發展現況”,醫院雙月刊,47卷,2期,頁27-29,4月。
2.林嬪嬙,2014,“臺灣智慧醫療推展現況”,醫療品質雜誌,8卷,3期,頁22-23。
3.陳亮恭,李威儒,2017,“智慧醫療數位轉型與再進化”,國土及公共治理季刊,5卷,4期,頁38-43。
4.張進,張建軍,張苗,吳鋒,韋麗,2017,“2型糖尿病漏誤診原因分析”,臨床誤診誤治,30卷,5期,頁38-40。
5.黄勇,2018,“探討骨折患者放射診斷誤診原因研究”,特别健康,14期,頁18-19。
6.廖述賢,宋怡貞,2008,“知識型決策支援系統應用於家庭醫師疾病診斷與病患關係管理之研究”,電子商務學報,10卷,1期,頁63-92。
7.趙君傑,侯全益,侯甚光,2016,“美國遠距醫療及遠距照護加護病房”,台灣醫學,20卷,4期,頁427-432。
8.鲍淑娣,張元亭,2004,“遠程醫療:穿戴式生物醫療儀器”,中國醫療器械信息,10卷,5期,頁1-3。
9.DigiTimes,2012,“以智慧運算輔助醫療決策 開創智慧醫療新契機”,網址https://www.digitimes.com.tw/iot/article.asp?cat=130&cat1=50&cat2=20&id=0000300861_2g67s91a706q7o09h0d9i,檢索日期:2018年4月23日。
10.Atanassov, A., & Antonov, L., 2012, “Comparative analysis of case based reasoning software frameworks jCOLIBRI and myCBR”, Journal of the University of Chemical Technology & Metallurgy, 47(1), pp.83-90.
11.Apanasik, Y., Shabalina, I., Kuznetsova, L., & Kuznetsov, V., 2012, “Decision support information system for hardly diagnosing diseases”, 2012 12th Conference of open Innovations Association (FRUCT).
12.Berner, E. S., & Graber, M. L., 2008, “Overconfidence as a cause of diagnostic error in medicine”, The American journal of medicine, 121(5), pp.S2-S23.
13.Banaee, H., Ahmed, M. U., & Loutfi, A., 2013, “Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges”, Sensors, 13(12), pp.17472-17500.
14.Du, H., 2015, “Analysis of misdiagnosis cases for acute abdomen cardiovascular disease”, Advanced Emergency Medicine, 4(4), pp.26-29.
15.Deng, P. S., 1994, “Using case-based reasoning for decision support”, IEEE, 4, pp.552-561.
16.Delone, W. H., & McLean, E. R., 2003, “The DeLone and McLean model of information systems success: a ten-year update”, Journal of management information systems, 19(4), pp.9-30.
17.Fouad, H., 2014, “Continuous health-monitoring for early detection of patient by web telemedicine system”, In International Conference on Circuits, Systems and Signal Processing, Saint Petersburg State Politechnical University.
18.Hunt, D. L., Haynes, R. B., Hanna, S. E., & Smith, K., 1998, “Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review”, Jama, 280(15), pp.1339-1346.
19.Iliff, E. C., 2015, “Matrix interface for medical diagnostic and treatment advice system and method”, U.S. Patent No. 9,081,879. Washington, DC: U.S. Patent and Trademark Office.
20.Jordan, R., Lam, J., Lyren, A., Sims, N., & Yang, C., 2017, “Actionable patient safety solution (APSS)# 3A: Medication errors”, Patient Safety Movement Foundation, pp.1-10.
21.Keen, P. G., 1978, “Decision support systems; an organizational perspective”, Sloan Management Review, 20(2), pp.81-82.
22.Krumholz, H. M., 2014, “Big data and new knowledge in medicine: the thinking, training, and tools needed for a learning health system”, Health Affairs, 33(7), pp.1163-1170.
23.Lee, C. S., & Wang, M. H., 2011, “A fuzzy expert system for diabetes decision support application”, IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 41(1), pp.139-153.
24.Liao, S. H., 2005, “Expert system methodologies and applications—a decade review from 1995 to 2004”, Expert systems with applications, 28(1), pp.93-103.
25.Musen, M. A., Middleton, B., & Greenes, R. A., 2014, “Clinical decision-support systems”, Biomedical informatics, Springer, London, pp.643-674.
26.Martinsons, M. G., & Davison, R. M., 2007, “Strategic decision making and support systems: Comparing American, Japanese and Chinese management” Decision Support Systems, 43(1), pp.284-300.
27.Meléndez, J., Colomer, J., & Macaya, D., 2001, “Case based reasoning methodology for supervision”, In Control Conference (ECC), pp. 1600-1605.
28.Mysiak, J., Giupponi, C., & Rosato, P., 2005, “Towards the development of a decision support system for water resource management”, Environmental Modelling & Software, 20(2), pp.203-214.
29.National Academies of Sciences, Engineering, and Medicine, 2016, “Improving diagnosis in health care”, National Academies Press.
30.Povoroznyuk, A. I., Filatova, A. E., Surtel, W., Burlibay, A., & Zhassandykyzy, M., 2015, “Design of decision support system when undertaking medical-diagnostic action”, Optical Fibers and Their Applications, 9816, pp.98161O1- 98161O7.
31.Power, D. J., & Sharda, R., 2007, “Model-driven decision support systems: concepts and research directions”, Decision Support Systems, 43(3), pp.1044-1061.
32.Pramanik, M. I., Lau, R. Y., Demirkan, H., & Azad, M. A. K., 2017, “Smart health: Big data enabled health paradigm within smart cities”, Expert Systems with Applications, 87, pp.370-383.
33.Ryan, Cristín., et al., 2014, “Prevalence and causes of prescribing errors: the Prescribing outcomes for trainee doctors engaged in clinical training (PROTECT) study”, Plos One, 9(1), pp. e79802.
34.Ribière, V., LaSalle, A. J., Khorramshahgol, R., & Gousty, Y., 1999, “Hospital information systems quality: a customer satisfaction assessment tool”, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences.
35.Sliwa, J., 2015, “Statistical challenges for quality assessment of smart medical devices”, 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), pp.380-385.
36.Singh, H., Thomas, E. J., Khan, M. M., & Petersen, L. A, 2007, “Identifying diagnostic errors in primary care using an electronic screening algorithm”, Archives of Internal Medicine, 167(3), pp.302-308.
37.Shah, Abhay, et al., 2018, “Susceptibility to misdiagnosis of adversarial images by deep learning based retinal image analysis algorithms”, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp.1454-1457.
38.Sudha, M., 2017, “Evolutionary and neural computing based decision support system for disease diagnosis from clinical data sets in medical practice”, Journal of medical systems, 41(11), pp.178.
39.Sicari, S., Rizzardi, A., Grieco, L. A., Piro, G., & Coen-Porisini, A., 2017, “A policy enforcement framework for Internet of Things applications in the smart health”, Smart Health, 3(4), pp.39-74.
40.Solanas, Agusti, et al., 2014, “Smart health: a context-aware health paradigm within smart cities”, IEEE Communications Magazine, 52(8), pp.74-81.
41.Tate, A , et al., 2006, “Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra”, NMR in Biomedicine, 19(4), pp.411-434.
42.Tsipouras, M. G., Exarchos, T. P., Fotiadis, D. I., Kotsia, A., Naka, A., & Michalis, L. K., 2006, “A decision support system for the diagnosis of coronary artery disease”, 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06), pp.279-284.
43.Vaghasiya, K., Sharma, A., & Verma, R. K., 2016, “Misdiagnosis murder: Disguised tb or lung cancer”, Pulm Res Respir Med Open J, 3(2), e5-e6.
44.Varshney, U., 2014, “Mobile health: Four emerging themes of research”, Decision Support Systems, 66, pp.20-35.
45.Wilk, P. J., 1995, “Medical diagnosis system and method”, U.S. Patent No. 5,437,278. Washington, DC: U.S. Patent and Trademark Office.
46.West, D., Mangiameli, P., Rampal, R., & West, V., 2005, “Ensemble strategies for a medical diagnostic decision support system: A breast cancer diagnosis application”, European Journal of Operational Research, 162(2), pp.532-551.
47.Yang, C. C., Leroy, G., & Ananiadou, S., 2013, “Smart health and wellbeing”, ACM Transactions on Management Information Systems (TMIS), 4(4), pp. 15:1-15:8.
48.Yan, H., Jiang, Y., Zheng, J., Peng, C., & Li, Q., 2006, “A multilayer perceptron-based medical decision support system for heart disease diagnosis”, Expert Systems with Applications, 30(2), pp.272-281.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊