||[AD94] H. Almuallim, and T. Dietterich, “Learning Boolean concepts in the presence of many irrelevant features,” Artificial Intelligence, Vol. 69 No. 1-2, 1994.|
[AGL98] R. Agrawal, D. Gunopulos, and F. Leymann, “Mining Process Models from Workflow Logs,” Proceedings of the International Conference on Extending Database Technology (EDBT), 1998.
[AL88] D. Angluin, and P. Laird, “Learning from noisy examples,” Machine Learning, Vol. 2, 1988.
[AS94] R. Agrawal, and R. Srikant, “Fast Algorithms for Mining Association Rules,” Proceedings of the International conference on Very Large Data Bases, 1994.
[AS95] R. Agrawal and R. Srikant, “Mining Sequential Patterns,” Proceedings of International Conference on Data Engineering, 1995.
[BD99] K. Bennett and A. Demiriz, “Semi-supervised support vector machines,” Advances in Neural Information Processing Systems, Vol. 11, 1999.
[BL97] A. Blum, and P. Langley, “Selection of relevant features and examples in machine learning,” Artificial Intelligence, 1997.
[BM98] A. Blum and T. Mitchell, “Combining labeled and unlabeled data with co-training,” Proceedings of International Conference on Computational Learning Theory, 1998.
[BNHI] The Bureau of National Health Insurance (BNHI). Http://www.nhi.org.tw.
[Brodley93] C. E. Brodley, “Addressing the Selective Superiority Problem: Automatic Algorithm/Model Class Selection,” Proceedings of International Conference on Machine Learning, 1993.
[BWJ98] C. Bettini, X.S. Wang, S. Jajodia, and J.L. Lin, “Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences,” IEEE Transactions on Knowledge and Data Engineering, Vol. 10, No. 2, 1998.
[CC02] F. G. Cozman and I. Cohen, “Unlabeled Data Can Degrade Classification Performance of Generative Classifiers,” Proceedings of International Conference on Artificial Intelligence, 2002.
[CF94] R. Caruana, and D. Freitag, “Greedy attribute selection,” Proceedings of International Conference on Machine Learning, 1994.
[CH00] D.J. Cook and L.B. Holder, “Graph-based Data Mining,” IEEE Intelligent Systems, Vol. 15, No. 2, 2000.
[CLR89] T.H. Cormen, C.E. Leiserson, and R.L. Rivest, “Introduction to Algorithms”, MIT Press, 1989.
[Datta98] A. Datta, “Automating the Discovery of AS-IS Business Process Models: Probabilistic and Algorithmic Approaches,” Information Systems Research, Vol. 9 No. 3, 1998.
[DH73] R. Duda, and P. hart, “Pattern Clasification and Scene Analysis,” Wiley, 1973.
[Fukunaga90] K. Fukunaga, “Introduction to Statistical Pattern Recognition,” Academic Press, 1990.
[FW97] C. P. Friedman and J. C. Wyatt, “Evaluation Methods in Medical Informatics,” Springer-Verlag, 1997.
[Glaser91] W. Glaser, “Health insurance in practice: international variations in financing, benefits, and problems,” San Francisco: Jossey-Bass Publisher, 1991.
[Guinane97] C. Guinane, “Clinical care pathways: tools and methods for designing, implementing, and analyzing efficient care practices,” New York: McGraw-Hill, 1997.
[HAIPAP98] L. Healy, M. Ayers, R. Iorio, D. Patch, D. Appleby, and B. Pfeifer, “Impact of a Clinical Pathways and Implant Standardization on Total Hip Arthroplasty,” The Journal of Arthroplasty, Vol. 13 No. 3, 1998.
[Hall96] C. Hall, “Intelligent Data Mining at IBM: New Products and Applications,” Intelligent Software Strategies, Vol. 7 No. 5, 1996.
[HJU90] K. Hogue, C. Jensen, and K. Urban, “The complete guide to health insurance: how to beat the high cost of being sick,” New York: Avon Books, 1990.
[HWGH97] H. He, J. Wang, W. Graco, and S. Hawkins, “Application of Neural Networks to Detection of Medical Fraud,” Expert Systems with Applications, Vol. 13 No. 4, 1997.
[HY02] S. –Y. Hang, and W.-S. Yang, “On the Discovery of Process Models from Their Instances,” Decision Support Systems, Vol. 34 No. 1 , 2002.
[Ireson97] C. Ireson, “Critical Pathways: Effectiveness in Achieving Patient Outcomes,” The Journal of Nursing Administration, Vol. 27 No. 6, 1997.
[JKP94] G. John, R. Kohavi, and K. Pfleger, “Irrelevant features and the subset selection problem,” Proceedings of International Conference on Machine Learning, 1994
[Joachines99] T. Joachines, “Transductive Inference for Text Classification using Support Vector Machines,” Proceedings of International Conference on Machine Learning, 1999.
[JW92] R. Johnson, and D. Wichern, “Applied Multivariate Statistical Analysis,” Englewood Cliffs: Prentice-Hall, 1992.
[KL51] S. Kullback, and R. Leibler, “On information and sufficiency,” Annals of Mathematical Statistics, Vol. 22, 1951.
[KR92] K. Kira and L. Rendell, “The feature selection problem: Traditional methods and a new algorithm,” Proceedings of the Conference on Artificial Intelligence (AAAI), 1992.
[KS96] D. Koller and M. Sahami, “Toward Optimal Feature Selection,” Proceedings of International Conference on Machine Learning, 1996.
[KV94] M. Keans and U. Vazarini, “An introduction to computational learning theory,” MIT Press, 1994.
[Lan00] C. H. Lan, “A Data Mining Technique Combining Fuzzy Sets Theory and Bayesian Classifier- An Application of Auditing the Health Insurance Fee for the National Health Insurance,” a thesis in Yuan-Ze University, 2000.
[Lavrac99] N. Lavrac, “Selected techniques for data mining in medicine,” Artificial Intelligence in Medicine, Vol. 16, 1999.
[LHM98] B. Liu, W. Hsu, and Y. Ma, “Integrating Classification and Association Rule Mining,” Proceedings of International Conference on Knowledge Discovery and Data Mining, 1998.
[LLM97] M. Lassey, W. Lassey, and M. Jinks, “Health care systems around the world: characteristics, issues, reforms,” Upper Saddle River: Prentice Hall, 1997.
[LS94] P. Langley, and S. Sage, “Induction of selective Bayesian classifiers,” Proceedings of the AAAI Symposium on Relevance, 1994.
[NELH] National Electronic Library for Health. Http://www.nelh.shef.ac.uk
[NG00] K. Nigam and R. Ghani, “Analyzing the effectiveness and applicability in co-training, ” Proceedings of International Conference on Information and Knowledge Management, 2000.
[NHCAA91] “Guidelines to Health Care Fraud,” REPORT, National Health Care Anti-Fraud Association (NHCAA), 1991.
[NHCAA02] “Health Care Fraud: A Serious and Costly Reality for All Americans,” REPORT all_about_hcf, National Health Care Anti-Fraud Association (NHCAA), 2002.
[NMTM00] K. Nigam, A. Mccalum, S. Thrun, and T. Mitchell, “Text Classification from Labeled and Unlabeled Documents using EM,” Machine Learning, Vol. 34, 2000.
[Pearl88] J. Pearl, “Probabilistic Reasoning in Intelligent Systems,” San Mateo: Morgan Kaufmann, 1988.
[PN89] P. Clark, and T. Niblett, “The CN2 Induction Algorithm”, Machine Learning Journal, Vol. 3 No. 4, 1989.
[Quinlan93] J. Quinlan, “C4.5: Programs for Machine Learning,” Los Altos: Morgan Kaufmann, 1993.
[RHW86] D. Rumelhart, G. Hinton, and R. Williams, “Learning Internal Representations by Error Propagation, Parallel Distributed Processing: Explorations in the Microstructures of Cognition,” MIT Press, 1986.
[SA96] R. Srikant and R. Agrawal, “Mining Sequential Patterns: Generalizations and Performance Improvements,” Proceedings of the 5th International Conference on Extending Database Technology (EDBT), 1996.
[SCL99] T. Sung, N. Chang and G. Lee, “Dynamics of Modeling in Data Mining: Interpretive Approach to Bankruptcy Prediction,” Journal of Management Information Systems, Vol. 16 No. 1, 1999.
[SGWRJ01] L. Sokol, B. Garcia, M. West, J. Rodriguez, and K. Johnson, “Precursory Steps to Mining HCFA Health Care Claims,” Proceedings of the Hawaii International Conference on System Sciences, 2001.
[Sokol98] L. Sokol, “Using data mining to support health care fraud detection,” Proceedings of the International Conference on the Practical Application of Knowledge Discovery and Data Mining (PADD), 1998.
[Ting94] K. M. Ting, “The problem of small disjuncts: its remedy in decision trees,” Proceedings of Canadian Conference on Artificial Intelligence, 1994.
[WA96] V. William and B. Archer, “Medicare program: changes to the hospital inpatient prospective payment systems and fiscal year rates,” REPORT RIN: 0938-AH34, The United States General Accounting Office, 1996.
[WH99] Y. Wu and T. S. Huang, “Using unlabeled data in supervised learning by discriminate-EM algorithm,” Proceedings of the Workshop on Using Unlabeled Data for Supervised Learning, 1999.
[ZO00] T. Zhang and F. J. Oles, “A probability analysis on the value of unlabeled data for classification problem,” Proceedings of International Conference on Machine Learning, 2000.