布里氏评分
谵妄
医学
逻辑回归
接收机工作特性
随机森林
髋部骨折
机器学习
支持向量机
梯度升压
心理干预
人工智能
内科学
计算机科学
重症监护医学
精神科
骨质疏松症
作者
Weili Zhang,Nan Tang,Jie Song,Mi Kyung Song,Qingqing Su,Xiaojie Fu,Yuan Gao
标识
DOI:10.1093/gerona/glaf200
摘要
An ML-based model was developed and validated to predict postoperative delirium risk in older patients with hip fracture. These findings may help to develop personalized interventions to provide better treatment plans and optimal resource allocation. The interpretable framework can increase the transparency of the model and facilitate understanding the reliability of the predictive model for the physicians.
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