Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity

Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potential to augment clinical decision-making and enhance quality care and precision medicine efforts, but also the potential to worsen existing health disparities without a thoughtful, transparent, and incl...

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Detalles Bibliográficos
Autores principales: Dankwa-Mullan, Irene, Weeraratne, Dilhan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2022
Materias:
In Focus
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9662931/
https://www.ncbi.nlm.nih.gov/pubmed/35652218
http://dx.doi.org/10.1158/2159-8290.CD-22-0373
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author Dankwa-Mullan, Irene
Weeraratne, Dilhan
author_facet Dankwa-Mullan, Irene
Weeraratne, Dilhan
author_sort Dankwa-Mullan, Irene
collection PubMed
description Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potential to augment clinical decision-making and enhance quality care and precision medicine efforts, but also the potential to worsen existing health disparities without a thoughtful, transparent, and inclusive approach that includes addressing bias in their design and implementation along the cancer discovery and care continuum. We discuss applications of AI/ML tools in cancer and provide recommendations for addressing and mitigating potential bias with AI and ML technologies while promoting cancer health equity.
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spelling pubmed-96629312023-01-05 Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity Dankwa-Mullan, Irene Weeraratne, Dilhan Cancer Discov In Focus Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potential to augment clinical decision-making and enhance quality care and precision medicine efforts, but also the potential to worsen existing health disparities without a thoughtful, transparent, and inclusive approach that includes addressing bias in their design and implementation along the cancer discovery and care continuum. We discuss applications of AI/ML tools in cancer and provide recommendations for addressing and mitigating potential bias with AI and ML technologies while promoting cancer health equity. American Association for Cancer Research 2022-06-02 2022-06-02 /pmc/articles/PMC9662931/ /pubmed/35652218 http://dx.doi.org/10.1158/2159-8290.CD-22-0373 Text en ©2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
spellingShingle In Focus
Dankwa-Mullan, Irene
Weeraratne, Dilhan
Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
title Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
title_full Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
title_fullStr Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
title_full_unstemmed Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
title_short Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
title_sort artificial intelligence and machine learning technologies in cancer care: addressing disparities, bias, and data diversity
topic In Focus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9662931/
https://www.ncbi.nlm.nih.gov/pubmed/35652218
http://dx.doi.org/10.1158/2159-8290.CD-22-0373
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