Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis

The threats to people's health from chronic diseases are always exist and increasing gradually. How to decrease these threats is an important issue in medical treatment. Thus, this paper suggests a model of a chronic diseases prognosis and diagnosis system integrating data mining (DM) and case-based reasoning (CBR). The main processes of the system include: (1) adopting data mining techniques to discover the implicit meaningful rules from health examination data, (2) using the extracted rules for the specific chronic diseases prognosis, (3) employing CBR to support the chronic diseases diagnosis and treatments, and (4) expanding these processes to work within a system for the convenience of chronic diseases knowledge creating, organizing, refining, and sharing. The experiment data are collected from a professional health examination center, MJ health screening center, and implemented through the system for analysis. The findings are considered as helpful references for doctors and patients in chronic diseases treatments.

[1]  Andrew Kusiak,et al.  Predicting survival time for kidney dialysis patients: a data mining approach , 2005, Comput. Biol. Medicine.

[2]  Christopher G. Chute,et al.  Prospective recruitment of patients with congestive heart failure using an ad-hoc binary classifier , 2005, J. Biomed. Informatics.

[3]  Riccardo Bellazzi,et al.  Temporal data mining for the quality assessment of hemodialysis services , 2005, Artif. Intell. Medicine.

[4]  Lothar Gierl,et al.  Integrating consultation and semi-automatic knowledge acquisition in a prototype-based architecture: experiences with dysmorphic syndromes , 1994, Artif. Intell. Medicine.

[5]  Rajeev Motwani,et al.  Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.

[6]  Ernesto Costa,et al.  Machine Learning, Explanation-Based Learning and Intelligent Tutoring Systems , 1992 .

[7]  Tong Heng Lee,et al.  Evolutionary computing for knowledge discovery in medical diagnosis , 2003, Artif. Intell. Medicine.

[8]  Krzysztof J. Cios,et al.  Uniqueness of medical data mining , 2002, Artif. Intell. Medicine.

[9]  Igor Kononenko,et al.  Machine learning in prognosis of the femoral neck fracture recovery , 1996, Artif. Intell. Medicine.

[10]  Juan Pedro Caraça-Valente,et al.  Combining expert knowledge and data mining in a medical diagnosis domain , 2002, Expert Syst. Appl..

[11]  Thomas Ellman,et al.  Explanation-based learning: a survey of programs and perspectives , 1989, CSUR.

[12]  Frank Puppe,et al.  Generated Critic in the Knowledge Based Neurology Trainer , 1995, AIME.

[13]  K.J. Cios,et al.  Issues in automating cardiac SPECT diagnosis , 2000, IEEE Engineering in Medicine and Biology Magazine.

[14]  Igor Kononenko,et al.  Machine learning for medical diagnosis: history, state of the art and perspective , 2001, Artif. Intell. Medicine.

[15]  Adelinde M. Uhrmacher,et al.  Case-based prediction in experimental medical studies , 1999, Artif. Intell. Medicine.

[16]  Evans Cd,et al.  A case-based assistant for diagnosis and analysis of dysmorphic syndromes , 1995 .

[17]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1989, IJCAI 1989.

[18]  John Zeleznikow,et al.  The Application of Case-Based Reasoning to the Tasks of Health Care Planning , 1993, EWCBR.

[19]  M. Frize,et al.  Clinical decision-support systems for intensive care units using case-based reasoning. , 2000, Medical engineering & physics.

[20]  U Wenkebach,et al.  Visualization of large datasets in intensive care. , 1992, Proceedings. Symposium on Computer Applications in Medical Care.

[21]  Rainer Schmidt,et al.  Case-based reasoning for antibiotics therapy advice: an investigation of retrieval algorithms and prototypes , 2001, Artif. Intell. Medicine.

[22]  Cheng-Seen Ho,et al.  A new hybrid case-based architecture for medical diagnosis , 2004, Inf. Sci..

[23]  RadhaKanta Mahapatra,et al.  Business data mining - a machine learning perspective , 2001, Inf. Manag..

[24]  Chun-Lang Chang,et al.  Using case-based reasoning to diagnostic screening of children with developmental delay , 2005, Expert Syst. Appl..

[25]  Efraim Turban,et al.  Integrating knowledge management into enterprise environments for the next generation decision support , 2002, Decis. Support Syst..

[26]  Johanna Gunnlaugsdottir,et al.  Seek and you will find, share and you will benefit: organising knowledge using groupware systems , 2003, Int. J. Inf. Manag..

[27]  Kristian J. Hammond,et al.  Chapter 8 – Case-based Planning , 1989 .

[28]  Rainer Schmidt,et al.  Medical multiparametric time course prognoses applied to kidney function assessments , 1999, Int. J. Medical Informatics.

[29]  Padhraic Smyth,et al.  Knowledge Discovery and Data Mining: Towards a Unifying Framework , 1996, KDD.

[30]  Robert T. Macura,et al.  MacRad: Radiology Image Resource with a Case-Based Retrieval System , 1995, ICCBR.

[31]  Melody Y. Kiang,et al.  Knowledge acquisition from an incomplete domain theory — An application on the Stock Market , 1992 .

[32]  Phyllis Koton,et al.  Reasoning about Evidence in Causal Explanations , 1988, AAAI.

[33]  Walter Kintsch.  The potential of latent semantic analysis for machine grading of clinical case summaries , 2002, J. Biomed. Informatics.

[34]  S. Daskalaki,et al.  Data mining for decision support on customer insolvency in telecommunications business , 2003, Eur. J. Oper. Res..

[35]  Paul H. J. Hendriks,et al.  Knowledge-based systems and knowledge management: Friends or foes? , 1999, Inf. Manag..

[36]  B López,et al.  Case-based learning of plans and goal states in medical diagnosis , 1997, Artif. Intell. Medicine.

[37]  Ting-Ping Liang,et al.  Special Section: Research in Integrating Learning Capabilities into Information Systems , 1993, J. Manag. Inf. Syst..

[38]  Lukasz A. Kurgan,et al.  Knowledge discovery approach to automated cardiac SPECT diagnosis , 2001, Artif. Intell. Medicine.

[39]  Rudy Setiono,et al.  Extracting rules from pruned networks for breast cancer diagnosis , 1996, Artif. Intell. Medicine.

[40]  Alex A. Freitas,et al.  A survey of evolutionary algorithms for data mining and knowledge discovery , 2003 .

[41]  Irma Becerra-Fernandez.  The role of artificial intelligence technologies in the implementation of People-Finder knowledge management systems , 2000, Knowl. Based Syst..

[42]  Christian Böhm,et al.  Modelling of classification rules on metabolic patterns including machine learning and expert knowledge , 2005, J. Biomed. Informatics.