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Pathways to breast cancer screening artificial intelligence algorithm validation
As more artificial intelligence (AI)-enhanced mammography screening tools enter the clinical market, greater focus will be placed on external validation in diverse patient populations. In this viewpoint, we outline lessons learned from prior efforts in this field, the need to validate algorithms on...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061055/ https://www.ncbi.nlm.nih.gov/pubmed/31540699 http://dx.doi.org/10.1016/j.breast.2019.09.005 |
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author | Lee, Christoph I. Houssami, Nehmat Elmore, Joann G. Buist, Diana S.M. |
author_facet | Lee, Christoph I. Houssami, Nehmat Elmore, Joann G. Buist, Diana S.M. |
author_sort | Lee, Christoph I. |
collection | PubMed |
description | As more artificial intelligence (AI)-enhanced mammography screening tools enter the clinical market, greater focus will be placed on external validation in diverse patient populations. In this viewpoint, we outline lessons learned from prior efforts in this field, the need to validate algorithms on newer screening technologies and diverse patient populations, and conclude by discussing the need for a framework for continuous monitoring and recalibration of these AI tools. Sufficient validation and continuous monitoring of emerging AI tools for breast cancer screening will require greater stakeholder engagement and the creation of shared policies and guidelines. |
format | Online Article Text |
id | pubmed-7061055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-70610552020-07-29 Pathways to breast cancer screening artificial intelligence algorithm validation Lee, Christoph I. Houssami, Nehmat Elmore, Joann G. Buist, Diana S.M. Breast Virtual special issue: Artificial Intelligence in Breast Cancer Care; Edited by Nehmat Houssami, Maria João Cardoso, Giuseppe Pozzi and Brigitte Seroussi As more artificial intelligence (AI)-enhanced mammography screening tools enter the clinical market, greater focus will be placed on external validation in diverse patient populations. In this viewpoint, we outline lessons learned from prior efforts in this field, the need to validate algorithms on newer screening technologies and diverse patient populations, and conclude by discussing the need for a framework for continuous monitoring and recalibration of these AI tools. Sufficient validation and continuous monitoring of emerging AI tools for breast cancer screening will require greater stakeholder engagement and the creation of shared policies and guidelines. Elsevier 2019-09-09 /pmc/articles/PMC7061055/ /pubmed/31540699 http://dx.doi.org/10.1016/j.breast.2019.09.005 Text en © 2019 Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Virtual special issue: Artificial Intelligence in Breast Cancer Care; Edited by Nehmat Houssami, Maria João Cardoso, Giuseppe Pozzi and Brigitte Seroussi Lee, Christoph I. Houssami, Nehmat Elmore, Joann G. Buist, Diana S.M. Pathways to breast cancer screening artificial intelligence algorithm validation |
title | Pathways to breast cancer screening artificial intelligence algorithm validation |
title_full | Pathways to breast cancer screening artificial intelligence algorithm validation |
title_fullStr | Pathways to breast cancer screening artificial intelligence algorithm validation |
title_full_unstemmed | Pathways to breast cancer screening artificial intelligence algorithm validation |
title_short | Pathways to breast cancer screening artificial intelligence algorithm validation |
title_sort | pathways to breast cancer screening artificial intelligence algorithm validation |
topic | Virtual special issue: Artificial Intelligence in Breast Cancer Care; Edited by Nehmat Houssami, Maria João Cardoso, Giuseppe Pozzi and Brigitte Seroussi |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061055/ https://www.ncbi.nlm.nih.gov/pubmed/31540699 http://dx.doi.org/10.1016/j.breast.2019.09.005 |
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