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研究生： 陳佳平
Chia-Ping Chen
論文名稱： 以貝式網路為基礎建立模型預測肺癌病人的醫療費用與存活時間
Predicting medical expenditure and survivability of the lung cancer patient by Bayesian network
指導教授： 王孔政
Kung-Jeng Wang
口試委員: 林希偉
Shi-Woei Lin
鄧乃嘉
Teng Nai-Chia
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業管理系
Department of Industrial Management
論文出版年： 2016
畢業學年度： 104
語文別： 英文
論文頁數： 64
中文關鍵詞： 高斯貝式網路 、肺癌 、醫療費用 、存活時間
外文關鍵詞： Conditional Gaussian Bayesian network, lung cancer, medical expenditure, survivability
相關次數： 點閱：243  下載：7 
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    • 肺癌是導致死亡的主要因素，高斯貝式網路建立預測肺癌病人的存活時間和醫療支出，本研究使用健保局資料庫，且模型不僅考慮慢性疾病和治療影響，也提供存活時間和費用的機率密度函數，存活時間和費用的模型預測能力的調整R2也提升到80.37%和40.35%。

    Lung cancer leads to a major cause of death. This study presents a Conditional Gaussian Bayesian network to predict survival time and medical expenditure of the lung cancer patient. This study uses the subject data in National Health Insurance Research Database from 1995 to 2010. The model considers chronic diseases and treatment effect and provides the density function of survival time and expenditure. The prediction of survival time and expenditure is promising with adjust R2 of 80.37% and 40.35%.

    Contents 摘要 I Abstract II 致謝 III Content of Figure V Content of Table VI Chapter1 Introduction 1 1.1 Research background 1 1.2 Research motivation 2 1.3 Research objective 3 1.4 Research limitation 3 1.5 Thesis structure 4 Chapter2 Literature 5 2.1 Risk adjustment 5 2.2 The risk factor of lung cancer 9 2.3 Bayesian network 10 Chapter3 Model 12 3.1 Bayesian network 12 3.2 Variable 12 3.3 Graphical modelling 16 Chapter4 Materials and results 19 Chapter5 Result and discussion 22 Chapter6 Conclusion 41 References 42 Appendix A: Variables definition 46 Appendix B: Medical expenditure 47 Appendix C: Resulting conditional probability table of site 48 Appendix D: The probability of backstopping of survival time 50 Appendix E: The performance of adjusted-R2 of survival time 52 Appendix F: Resulting conditional probability table of site 52 Appendix G: The probability of backstopping of expenditure 54 Appendix H: The performance of adjusted-R2 of future expenditure 56

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