Publications (2)0 Total impact
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Article: Support Vector Regression-based Model to Analyze Prognosis of Infants with Congenital Muscular Torticollis.
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ABSTRACT: Congenital muscular torticollis, a common disorder that refers to the shortening of the sternocleidomastoid in infants, is sensitive to correction through physical therapy when treated early. If physical therapy is unsuccessful, surgery is required. In this study, we developed a support vector regression model for congenital muscular torticollis to investigate the prognosis of the physical therapy treatent in infants. Fifty-nine infants with congenital muscular torticollis received physical therapy until the degree of neck tilt was less than 5°. After treatment, the mass diameter was reevaluated. Based on the data, a support vector regression model was applied to predict the prognoses. 10-, 20-, and 50-fold cross-tabulation analyses for the proposed model were conducted based on support vector regression and conventional multi-regression method based on least squares. The proposed methodbased on support vector regression was robust and enabled the effective analysis of even a small amount of data containing outliers. The developed support vector regression model is an effective prognostic tool for infants with congenital muscular torticollis who receive physical therapy.Healthcare informatics research. 12/2010; 16(4):224-30. -
Article: Diagnostic analysis of patients with essential hypertension using association rule mining.
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ABSTRACT: The purpose of this study was to analyze the records of patients diagnosed with essential hypertension using association rule mining (ARM). Patients with essential hypertension (ICD code, I10) were extracted from a hospital's data warehouse and a data mart constructed for analysis. Apriori modeling of the ARM method and web node in the Clementine 12.0 program were used to analyze patient data. Patients diagnosed with essential hypertension totaled 5,022 and the diagnostic data extracted from those patients numbered 53,994. As a result of the web node, essential hypertension, non-insulin dependent diabetes mellitus (NIDDM), and cerebral infarction were shown to be associated. Based on the results of ARM, NIDDM (support, 35.15%; confidence, 100%) and cerebral infarction (support, 21.21%; confidence, 100%) were determined to be important diseases associated with essential hypertension. Essential hypertension was strongly associated with NIDDM and cerebral infarction. This study demonstrated the practicality of ARM in co-morbidity studies using a large clinic database.Healthcare informatics research. 06/2010; 16(2):77-81.
