外部有效性
计算机科学
预测建模
数据挖掘
机器学习
数据科学
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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