利用患者相似性建立个性化糖尿病预测模型

Establishing the Personalized Diabetes Prediction Models by Making Use of Patient Similarity

利用患者相似性筛选不同规模的研究队列,分别建立基于Logistic回归、决策树和BP神经网络的糖尿病个性化及非个性化预测模型,探讨基于患者相似性的个性化与非个性化疾病预测模型性能差异,以及基于不同机器学习算法的个性化预测模型性能差异。

By making use of patient similarity,the paper screens study cohort of various sizes,establishes personalized and non-personalized diabetes prediction models based on Logistics Regression(LR),Decision Tree(DT)and Back Propagation(BP)neural network,discusses the difference between the peifonnances of the personalized disease prediction model and the non-personalized one based on patient similarity,as well as the difference between the performances of personalized prediction models based on different machine learning algorithms.