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Podiatric Clinical Diagnosis using Decision Tree Data Mining  

Kim, Jin-Ho (Department of Healthcare Engineering, Chonbuk National University)
Park, In-Sik (Department of Healthcare Engineering, Chonbuk National University)
Kim, Bong-Ok (Department of Rehabilitation, Chungnam National University College of Medicine)
Yang, Yoon-Seok (Division of Biomedical Engineering, Chonbuk National University)
Won, Yong-Gwan (School of Electronics and Computer Engineering, Chonnam National University)
Kim, Jung-Ja (Division of Biomedical Engineering, Chonbuk National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.48, no.2, 2011 , pp. 28-37 More about this Journal
Abstract
With growing concerns about healthy life recently, although the podiatry which deals with the whole area for diagnosis, treatment of foot and leg, and prevention has been widely interested, research in our country is not active. Also, because most of the previous researches in data analysis performed the quantitative approaches, the reasonable level of reliability for clinical application could not be guaranteed. Clinical data mining utilizes various data mining analysis methods for clinical data, which provides decision support for expert's diagnosis and treatment for the patients. Because the decision tree can provide good explanation and description for the analysis procedure and is easy to interpret the results, it is simple to apply for clinical problems. This study investigate rules of item of diagnosis in disease types for adapting decision tree after collecting diagnosed data patients who are 2620 feet of 1310(males:633, females:677) in shoes clinic (department of rehabilitation medicine, Chungnam National University Hospital). and we classified 15 foot diseases followed factor of 22 foot diseases, which investigated diagnosis of 64 rules. Also, we analyzed and compared correlation relationship of characteristic of disease and factor in types through made decision tree from 5 class types(infants, child, adolescent, adult, total). Investigated results can be used qualitative and useful knowledge for clinical expert`s, also can be used tool for taking effective and accurate diagnosis.
Keywords
Clinical foot diagnosis; Foot deformity; Classification; Decision Tree; Induction rule;
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Times Cited By KSCI : 4  (Citation Analysis)
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