3种机器学习算法对维持性血液透析病人衰弱风险预测性能比较OACSTPCD
Comparison of value of risk assessment models based on three machine learning algorithms in predicting frailty risk among maintenance hemodialysis patients
目的:应用Logistic回归、决策树CART和随机森林3种机器学习算法分别构建维持性血液透析病人衰弱风险预测模型,比较3种模型的预测效果.方法:选取2021年10月—2022年3月在杭州市2家三级甲等医院接受维持性血液透析治疗的病人485例,按照7∶3的比例随机分为训练集(n=341)和测试集(n=144),运用Logistic回归、决策树CART和随机森林建立维持性血液透析病人衰弱风险预测模型,采用准确率、灵敏度、特异度、阳性预测值、阴性预测…查看全部>>
Objective:To compare the value of risk assessment models based on Logistic regression,decision tree and random forest machine learning algorithms in predicting frailty risk among maintenance hemodialysis patients.Methods:From October 2021 to March 2022,a total of 485 patients receiving maintenance hemodialysis treatment in two tertiary grade-A hospitals in Hangzhou were selected and treated according to 7∶3 ratio was randomly divided into training set(n=341)…查看全部>>
汪丹丹;姚侃斐;祝雪花
浙江中医药大学护理学院,浙江 310053浙江中医药大学护理学院,浙江 310053浙江中医药大学护理学院,浙江 310053
维持性血液透析衰弱预测模型Logistic回归决策树随机森林
maintenance hemodialysisfrailtyprediction modelLogistic regressiondecision treerandom forest
《护理研究》 2024 (1)
8-16,9
浙江省卫生健康科技计划项目,编号:2022KY221
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