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Patient Classification Model of Appendicitis Severity Based on Bayesian Stepwise Discriminant Analysis

机译:基于贝叶斯逐步判别分析的阑尾炎严重程度患者分类模型

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摘要

To emphasize distinctions in diagnosis and provide valuable guidance for treatment based on patient heterogeneity, it is useful to classify the various forms of appendicitis into three groups. A bayesian stepwise discriminant model was proposed to predict the patient's severity of Appendicitis. The age, BMI index, diabetes status, perforation status, other complications, WBC and hemoglobin index were discriminant factors for patient classification according to a bayesian stepwise discriminant analysis. The classification accuracies for severe appendicitis and mild appendicitis were 96% and 97% respectively. The results showed that the presented method was verified effective and practically applicable.
机译:为了强调诊断上的区别并为基于患者异质性的治疗提供有价值的指导,将各种形式的阑尾炎分为三类非常有用。提出了贝叶斯逐步判别模型来预测患者的阑尾炎严重程度。根据贝叶斯逐步判别分析,年龄,BMI指数,糖尿病状况,穿孔状况,其他并发症,WBC和血红蛋白指数是患者分类的判别因素。重度阑尾炎和轻度阑尾炎的分类准确率分别为96%和97%。结果表明,所提出的方法是有效和实用的。

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