본문 바로가기
HOME> 논문 > 논문 검색상세

논문 상세정보

경영정보학연구 = The journal of MIS research v.16 no.2, 2006년, pp.69 - 84   피인용횟수: 3

사례기반 추론을 이용한 암 환자 진료비 예측 모형의 개발
Development of a Medial Care Cost Prediction Model for Cancer Patients Using Case-Based Reasoning

정석훈   (고려대학교 경영대학UU0000159  ); 서용무   (고려대학교 경영대학UU0000159  );
  • 초록

    Importance of Today's diffusion of integrated hospital information systems is that various and huge amount of data is being accumulated in their database systems. Many researchers have studied utilizing such hospital data. While most researches were conducted mainly for medical diagnosis, there have been insufficient studies to develop medical care cost prediction model, especially using machine learning techniques. In this research, therefore, we built a medical care cost prediction model for cancer patients using CBR (Case-Based Reasoning), one of the machine learning techniques. Its performance was compared with those of Neural Networks and Decision Tree models. As a result of the experiment, the CBR prediction model was shown to be the best in general with respect to error rate and linearity between real values and predicted values. It is believed that the medical care cost prediction model can be utilized for the effective management of limited resources in hospitals.


  • 주제어

    Medical Data Mining .   Cost Prediction Model .   Case-Based Reasoning.  

  • 참고문헌 (38)

    1. Changchien, S.W. and Ming-Chin, L., 'Design and Implementation of a Case- Based Reasoning System for Marketing Plans,' Expert Systems with Applications, Vol. 28, 2005, pp. 43-53 
    2. Chun, S. and Yoon-Joo, P., 'Dynamic Adaptive Ensemble Case-Based Reasoning: Application to Stock Market Prediction,' Expert Systems with Application, Vol. 28, 2005, pp. 435-443 
    3. Fireman, B.H., Fehrenbacher, L., Gruskin E.P., and Ray, G.T., 'Cost of Cancer for Patients in Cancer Clinical Trials,' Journal of the National Cancer Institute, Vol. 92, No. 2, 2000, pp. 136-142 
    4. Fu, Y. and Ruimin, S., 'GA Based CBR Approach in Q&A System,' Expert Systems with Applications, Vol. 26, 2004, pp. 167-170 
    5. He, J., Hae-Jin, H., Robert, H., Phang, C. T., and Yi, P., 'Transmembrane Segments Prediction and Understanding Using Support Vector Machine and Decision Tree,' Expert Systems with Applications, Vol. 30, 2006, pp. 64-72 
    6. Ismael M.B., Eisenstein, E.L, and Hammond, W.E., 'A Comparison of Neural Network Models for the Prediction of The Cost of Care for Acute Coronary Syndrome Patients,' Proceedings of AMIA Symposium, 1998, pp. 533-537 
    7. Kira, K. and Rendall, L.A., 'A Practical Approach to Feature Selection,' Proceedings of the ninth International Conference on Machine Learning, Aberdeen, Scotland, UK, San Mateo: Morgan Kaufmann, 1992, pp. 249-256 
    8. Kohavi, R. and John, G.H., 'Wrappers for Feature Subset Selection,' Artificial Intelligence, Vol. 97, 1997, pp. 273-324 
    9. Penberthy, L., Retchin, S.M., McDonald, M.K., McClish, D.K., Desch, C.E., Riley, G.F., Smith, T.J., Hillner, B.E., and Newschaffer, C.J., 'Predictors of Medicare Costs in Elderly Beneficiaries with Breast, Colorectal, Lung, or Prostate Cancer,' Health Care Management Science, Vol. 2, 1999, pp. 146-160 
    10. Riesbeck, C.K. and Schank, R.L., Inside Case-based Reasoning, Lawrence Erlbaum Associates, 1989 
    11. Romero, C.E. and Jiefeng, S., 'Development of an Artificial Neural Network-Based Software for Prediction of Power Plant Canal Water Discharge Temperature,' Expert Systems with Applications, Vol. 29, 2005, pp. 831-838 
    12. Tollestrup, K., Frost, F.J., Stidley, C.A., Bedrick, E., McMillan, G., Kunde, T., and Petersen, H.V., 'The Excess Costs of Breast Cancer Health Care in Hispanic and Non-Hispanic Female Members of a Managed Care Organization,' Breast Cancer Research and Treatment, Vol. 66, 2001, pp. 25-31 
    13. 장남식, 홍성완, 장재호, 데이터 마이닝, 대청 출판사, 1999 
    14. Goldman, D.P., Schoenbaum, M.L., Potosky, A.L., Weeks, J.C., Berry, S.H., Escarce, J.J., Weidmer, B.A., Kilgore, M.L., Wagle, N., Adams, J.L., Figlin, R.A., Lewis, J.H., Cohen, J., Kaplan, R., and McCabe M., 'Measuring the Incremental Cost of Clinical Cancer Research,' Journal of Clinical Oncology, Vol. 19, No. 1, 2001, pp. 105-110 
    15. Kohavi, R., 'A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection, In S. Wermter, E. Riloff, & G. Scheler(Eds.),' The fourteenth international joint conference on artificial intelligence (IJCAI), Montreal, Quebec, Canada, San Francisco, CA: Morgan Kaufman Publishing, 1995, pp. 1137-1145 
    16. DeBerard, M.S., Kevin S.M., Alan, L.C., and Edward B.H., 'Presurgical Biopsychosocial Variables Predict Medical and Compensation Costs of Lumbar Fusion in Utah Workers' Compensation Patients,' The Spine Journal, Vol. 3, 2003, pp. 420-429 
    17. Kolodner, J., Case-Based Reasoning, Morgan Kaufmann publishers, Inc., 1993 
    18. Sheng, W.H., Wang, J.T., Lu, D.C.T., Chie, W.C., Chen, Y.C., and Chang, S.C., 'Comparative Impact of Hospital-Acquired Infections on Medical Costs, Length of Hospital Stay and Outcome between Community Hospitals and Medical Centres,' Journal of Hospital Infection, Vol. 59, 2005, pp. 205-214 
    19. Mangalampalli, A., Srirama, M.M., Rama, C., and Ajeet K.J., 'A Neural Network Based Clinical Decision-Support System for Efficient Diagnosis and Fuzzy-Based Prescription of Gynecological Diseases Using Homoeopathic Medicinal System,' Expert Systems with Applications, Vol. 30, 2006, pp. 109-116 
    20. Li, W.S. and Chris, C., 'SEMINT: A Tool for Identifying Attribute Correspondences in Heterogeneous Databases Using Neural Networks,' Data & Knowledge Engineering, Vol. 33, 2000, pp. 49-84 
    21. Tung, K., Ing-Chung, H., Shu-Ling, C., and Chih-Ting, S., 'Mining the Generation Xers' Job Attitudes by Artificial Neural Network and Decision Tree-Empirical Evidence in Taiwan,' Expert Systems with applications, Vol. 29, 2005, pp. 783-794 
    22. Enke, D. and Suraphan T., 'The Use of Data Mining and Neural Networks for Forecasting Stock Market Returns,' Expert Systems with Applications, Vol. 29, 2005, pp. 927-940 
    23. Berry, M.J.A. and Linoff, G., Data Mining Techniques, John Wiley & Sons, Inc., 1997 
    24. Martens, J., Geert W., Jan, V., and Christophe, M., 'An Initial Comparison of a Fuzzy Neural Classifier and a Decision Tree Based Classifier,' Expert Systems with Applications, Vol. 15, 1998, pp. 375-381 
    25. Cho, Y.H., Jae, K.K., and Soung, H.K., 'A Personalized Recommender System Based on Web Usage Mining and Decision Tree Induction,' Expert Systems with Applications, Vol. 23, 2002, pp. 329-342 
    26. Demsar, J., Zupan, B., Aoki, N., Wall, M.J., Granchi, T.H., and Beck, J.R., 'Feature Mining and Predictive Model Construction from Severe Trauma Patient's Data,' International Journal of Medical Informatics, Vol. 63, 2001, pp. 41-50 
    27. Jayadevappa, R., Sumedha, C., Mark, W., Bernard, S.B., and Bruce, M., 'Medical Care Cost of Patients with Prostate Cancer,' Urologic Oncology: Seminars and Original Investigations, Vol. 23, 2005, pp. 155-162 
    28. 한국 중앙 암 등록 본부, 한국중앙 암 등록 사업 연례 보고서, 보건 복지부, 2003 
    29. Jenn-Lung S., Guo-Zhen W., and I-Pin C., 'The Approach of Data Mining Methods for Medical Database,' Engineering in Medicine and Biology Society, Proceedings of the 23rd Annual International Conference of the IEEE, Vol. 4, 2001, pp. 3824-3826 
    30. Jerez-Aragones, J.M., Gomez-Ruiz, J.A., Ramos-Jimenez, G., Munoz-Perez, J., and Alba-Conejo, E., 'A Combined Neural Network and Decision Trees Model for Prognosis of Breast Cancer Relapse,' Artificial Intelligence in Medicine, Vol. 27, 2003, pp. 45-63 
    31. Sohn, S.Y., Yong K.J., and Seong, O.C., 'Classification Models for Sequential Flight Test Results for Selecting Air Force Pilot Trainee,' Expert Systems with Applications, Vol. 26, 2004, pp. 591-599 
    32. Masuda, G., Sakamoto, N., and Yamamoto, R., 'A Framework for Dynamic Evidence Based Medicine using Data Mining,' IEEE Symposium on Computer-Based Medical Systems, 2002, pp. 117-122 
    33. Tseng, H., Chien-Chen, C., and Shu-Hsuan, C., 'Applying Case-Based Reasoning for Product Configuration in Mass Customization Environments,' Expert Systems with Applications, Vol. 29, 2005, pp. 913-925 
    34. Mitchell, and Tom, M., 'Machine Learning and Data Mining,' Communications of the ACM, Vol. 42, No. 11, 1999 
    35. Roche, K., Paul, N., Smuck, B., Whitehead, M., Zee, B., Pater, J., Hiatt, M.A., and Walker, H., 'Factors Affecting Workload of Cancer Clinical Trials: Results of a Multicenter Study of the National Cancer Institute of Canada Clinical Trials Group,' Journal of Clinical Onclogy, Vol. 20, No. 2, 2002, pp. 545-556 
    36. Dash, M. and Liu, H., 'Feature Selection for Classification,' Intelligent Data Analysis, Vol. 1, 1997, pp. 131-156 
    37. Jeng, B., Jian-xun, C., and Ting-peng L., 'Applying Data Mining to Learn System Dynamics in a Biological Model,' Expert Systems with Applications, Vol. 30, 2006, pp. 50-58 
    38. Kowalski, Z., Maria, M., Stefan Z., and Marcin, D., 'CBR Methodology Application in an Expert System for Aided Design Ship'S Engine Room Automation,' Expert Systems with Applications, Vol. 29, 2005, pp. 256-263 
  • 이 논문을 인용한 문헌 (3)

    1. Yun, Jong-Cahn ; Youn, Sung-Dae 2007. "A Design of mCRM System using Case-Based Reasoning" 한국해양정보통신학회논문지 = The journal of the Korea Institute of Maritime Information & Communication Sciences, 11(10): 1886~1893     
    2. Yun, Jong-Chan ; Kim, Hak-Chul ; Kim, Jong-Jin ; Youn, Sung-Dae 2010. "A Study on the CBR Pattern using Similarity and the Euclidean Calculation Pattern" 한국해양정보통신학회논문지 = The journal of the Korea Institute of Maritime Information & Communication Sciences, 14(4): 875~885     
    3. Kim, Han-Kyoul ; Choi, Keun-Ho ; Lim, Sung-Won ; Rhee, Hyun-Sill 2016. "Development of Prediction Model for Prevalence of Metabolic Syndrome Using Data Mining: Korea National Health and Nutrition Examination Study" 디지털융복합연구 = Journal of digital convergence, 14(2): 325~332     

 저자의 다른 논문

  • 정석훈 (1)

    1. 2008 "신용카드 연체자 분류모형의 성능평가 척도 비교 : 예측률과 유틸리티 중심으로" Journal of information technology applications & management = 한국데이타베이스학회지 15 (4): 21~36    
  • 서용무 (20)

 활용도 분석

  • 상세보기

    amChart 영역
  • 원문보기

    amChart 영역

원문보기

무료다운로드
  • NDSL :
유료다운로드

유료 다운로드의 경우 해당 사이트의 정책에 따라 신규 회원가입, 로그인, 유료 구매 등이 필요할 수 있습니다. 해당 사이트에서 발생하는 귀하의 모든 정보활동은 NDSL의 서비스 정책과 무관합니다.

원문복사신청을 하시면, 일부 해외 인쇄학술지의 경우 외국학술지지원센터(FRIC)에서
무료 원문복사 서비스를 제공합니다.

NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.

이 논문과 함께 이용한 콘텐츠
이 논문과 함께 출판된 논문 + 더보기