外部有效性
计算机科学
预测建模
数据挖掘
机器学习
统计
数学
作者
Gary S. Collins,Paula Dhiman,Jie Ma,Michael Maia Schlüssel,Lucinda Archer,Ben Van Calster,Frank E. Harrell,Glen P. Martin,Karel G. M. Moons,Maarten van Smeden,Matthew Sperrin,Garrett S. Bullock,Richard D. Riley
标识
DOI:10.1136/bmj-2023-074819
摘要
Evaluating the performance of a clinical prediction model is crucial to establish its predictive accuracy in the populations and settings intended for use. In this article, the first in a three part series, Collins and colleagues describe the importance of a meaningful evaluation using internal, internal-external, and external validation, as well as exploring heterogeneity, fairness, and generalisability in model performance.
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