医学
预测值
泄漏
机器学习
经蝶手术
脑脊液漏
前瞻性队列研究
垂体腺瘤
随机森林
脑脊液漏
逻辑回归
试验预测值
队列
接收机工作特性
外科
内科学
脑脊液
腺瘤
计算机科学
工程类
环境工程
作者
Leonardo Tariciotti,Giorgio Fiore,Giorgio Carrabba,Giulio Bertani,Luigi Schisano,Stefano Borsa,Emanuele Ferrante,Valerio Maria Caccavella,Pier Paolo Mattogno,Martina Giordano,Giulia Remoli,Giovanna Mantovani,Marco Locatelli
标识
DOI:10.23736/s0390-5616.21.05295-4
摘要
The RF classifier showed the best performance across all models selected. RF models might predict surgical outcomes in heterogeneous multimorbid and fragile populations outperforming classical statistical analyses and other ML models (SVM, ANN etc.), improving patient management and reducing preventable morbidity and additional costs.
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