Perspectives on validation of clinical predictive algorithms

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 associ...

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Autores principales: de Hond, Anne A. H., Shah, Vaibhavi B., Kant, Ilse M. J., Van Calster, Ben, Steyerberg, Ewout W., Hernandez-Boussard, Tina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Comment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163568/
https://www.ncbi.nlm.nih.gov/pubmed/37149704
http://dx.doi.org/10.1038/s41746-023-00832-9
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author de Hond, Anne A. H.
Shah, Vaibhavi B.
Kant, Ilse M. J.
Van Calster, Ben
Steyerberg, Ewout W.
Hernandez-Boussard, Tina
author_facet de Hond, Anne A. H.
Shah, Vaibhavi B.
Kant, Ilse M. J.
Van Calster, Ben
Steyerberg, Ewout W.
Hernandez-Boussard, Tina
author_sort de Hond, Anne A. H.
collection PubMed
description 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.
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spelling pubmed-101635682023-05-08 Perspectives on validation of clinical predictive algorithms de Hond, Anne A. H. Shah, Vaibhavi B. Kant, Ilse M. J. Van Calster, Ben Steyerberg, Ewout W. Hernandez-Boussard, Tina NPJ Digit Med Comment 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. Nature Publishing Group UK 2023-05-06 /pmc/articles/PMC10163568/ /pubmed/37149704 http://dx.doi.org/10.1038/s41746-023-00832-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Comment
de Hond, Anne A. H.
Shah, Vaibhavi B.
Kant, Ilse M. J.
Van Calster, Ben
Steyerberg, Ewout W.
Hernandez-Boussard, Tina
Perspectives on validation of clinical predictive algorithms
title Perspectives on validation of clinical predictive algorithms
title_full Perspectives on validation of clinical predictive algorithms
title_fullStr Perspectives on validation of clinical predictive algorithms
title_full_unstemmed Perspectives on validation of clinical predictive algorithms
title_short Perspectives on validation of clinical predictive algorithms
title_sort perspectives on validation of clinical predictive algorithms
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163568/
https://www.ncbi.nlm.nih.gov/pubmed/37149704
http://dx.doi.org/10.1038/s41746-023-00832-9
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