中國醫藥大學機構典藏 China Medical University Repository, Taiwan:Item 310903500/43876
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    题名: EVALUATION OF INTELLIGENT SYSTEM TO THE CONTROL OF DIABETES
    作者: (SHOU-WEI CHIEN);(CHO-TSAN BAU);(KER-CHUNG LIN);(KUO-AN WAN);陳永福(Yung-Fu Chen)*;(JONG-CHEN CHEN)*
    贡献者: 公共衛生學院醫務管理學系
    关键词: Diabetes;Logistic regression analysis;Clinical decision support system;Neural network;Support vector machine;Recursive feature elimination;Decision tree;Radial basis function network
    日期: 2012-01
    上传时间: 2012-04-19 15:07:51 (UTC+8)
    摘要: Diabetes, which ranks 4th among the top ten causes of death in Taiwan, is
    one of the most important medical issues in the 21st century. However, for most diabetic
    patients, their blood sugar is not under good control, especially in ICUs. Good control of
    blood sugar may reduce the risk of sepsis to 34% for patients in ICUs. The importance of
    good blood sugar control for patients in ICUs is manifested by a signi cant reduction of
    mortality and morbidity. This study designed a clinical decision support system (CDSS)
    using a support vector machine (SVM) to predict if a critically ill patient can have good
    glucose control after insulin administration. A lter method based on logistic regression
    analysis (LRA) and a wrapper method based on recursive feature elimination (RFE) were
    adopted to select salient features from 10 variables for CDSS design. Data on 231 patients
    (2492 records) were collected covering four years from an ICU. Four signi cant variables
    (p < 0:05) using LRA in contrast to ve ones using RFE algorithm, were selected. The
    results show that the predictive accuracy under cross-validation was 93.50% for features
    selected with LRA, and the accuracy, sensitivity and speci city with SVM-RFE were
    95.75%, 92.71% and 99.81%, respectively. It could predict the outcome quite accurately
    after having injected a certain dose of insulin. The proposed system may help doctors
    effectively assess their patients in determining insulin dose for better glucose control in
    an ICU setting.
    關聯: International Journal of Innovative Computing Information and Control 8(1(B)):779-790
    显示于类别:[醫務管理學系暨碩士班] 期刊論文

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