| Summary: | 碩士 === 國立成功大學 === 工業與資訊管理學系專班 === 95 === Stroke is one of the life-threatening neuropathy. It is the key factor to increase mortality rate over the world. Two thousands five hundred million people suffered from stroke on earth. Among these figures, one hundred sixty thousand people died of stroke in America and ten thousand people died each year in Taiwan. Patients who had Transient ischaemic attack(TIA) suffered from recurrent stroke is ten times more. Their mortality rate is higher than one-fourth. Additionally, stroke recurrence is a significant concern with regard to an increase in mortality, disability, and length of hospital stay. Thus, correlation analysis can be used to look at the relationships between stroke risk factors and the severity score of recurrent stroke. This built system assist the physicians in diagnosis.
To predict the stroke recurrence is a complex task and it is a nonlinear relationship among many variables. We developed an ANN model to assist the physicians to predict the possibility of stroke recurrence. The study is retrospective by using information from a database of medical inpatients. Three hundred and thirty one patients’ records were used as sample. To achieve optimum performance, we use a three-fold cross validation procedure. Furthermore, we compared the performance of ANN against the logistic regression approach on the same dataset. Our results show that patients with well control blood pressure will have lower severity score. Finally, we evaluated the performance of models according to prediction accuracy, sensitivity and specificity.
|
|---|
