Perspectives on validation of clinical predictive algorithms

被引：22

作者：

de Hond, Anne A. H. ^{[1
,2
,3
]}

Shah, Vaibhavi B. B. ^{[2
]}

Kant, Ilse M. J. ^{[4
]}

Van Calster, Ben ^{[3
,5
]}

Steyerberg, Ewout W. ^{[1
,3
]}

Hernandez-Boussard, Tina ^{[2
,6
,7
]}

机构：

[1] Leiden Univ, Med Ctr, Clin AI Implementat & Res Lab, Leiden, Netherlands

[2] Stanford Univ, Dept Med Biomed Informat, Stanford, CA 94305 USA

[3] Leiden Univ, Med Ctr, Dept Biomed Data Sci, Leiden, Netherlands

[4] Univ Med Ctr Utrecht, Dept Digital Hlth, Utrecht, Netherlands

[5] Katholieke Univ Leuven, Dept Dev & Regenerat, Leuven, Belgium

[6] Stanford Univ, Dept Biomed Data Sci, Stanford, CA USA

[7] Stanford Univ, Dept Epidemiol & Populat Hlth by courtesy, Stanford, CA USA

来源：

NPJ DIGITAL MEDICINE | 2023年 / 6卷 / 01期

基金：

美国国家卫生研究院; 比利时弗兰德研究基金会;

关键词：

MODEL;

D O I：

10.1038/s41746-023-00832-9

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

The generalizability of predictive algorithms is of key relevance to application in clinical practice. We provide an overview of three types of generalizability, based on existing literature: temporal, geographical, and domain generalizability. These generalizability types are linked to their associated goals, methodology, and stakeholders.

引用

页数：3

共 22 条

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