| Summary: | 碩士 === 國立虎尾科技大學 === 工業管理系工業工程與管理碩士班 === 105 === Taiwan’s population structure presents an aging society. Due to the changed medical standard and health environments, the population age has gradually risen. Psoriasis with accompanying sleep disorder is a chronic disease. Chronic disease is the main cause of death for the elderly population. Cardiovascular disease is one of the ten leading causes of death in Taiwan. Research shows that hypertension, diabetes, hyperlipidemia, and alcoholism are conditions recognized as risk factors.
In this study, psoriasis patients with accompanying sleep disorder from the recent database of an anonymous medical institution were adopted as research participants. Through literature reviews and interviews with physicians, the important factors contributing to increased risk of cardiovascular disease were screened. Using the algorithm of artificial intelligence such as particle swarm optimization algorithm, genetic logistic regression algorithm, and cross entropy algorithm, the factor weights were calculated. The back propagation neural network and support vector machine were conjunctively used to construct six predictive models and three assessment systems to evaluate the risk of contracting cardiovascular disease. Research results show that although the particle swarm optimization algorithm combined with the case-based reasoning assessment system derive at higher accuracy, the Friedman’s test results show that the weights of the three algorithms produce no significant differences on the similarity calculation. Moreover, the accuracy and the area under the ROC curve reach above 83% and 0.812% respectively, indicating both are suitable for computing the assessment system weight. For the predictive model part, although the particle swarm optimization algorithm coupled with support vector machine produce higher accuracy, the ten-fold cross validation shows the average accuracy of 89.73% and the area under the ROC curve of 0.871. However, the six predictive models after the Friedman’s test show no significant differences. The research results shall be provided to medical institutions and clinical workers as references in aided diagnosis and for correct treatment to patients that will help lessen their disease load.
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