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Ethics of AI in Radiology: A Review of Ethical and Societal Implications

Artificial intelligence (AI) is being applied in medicine to improve healthcare and advance health equity. The application of AI-based technologies in radiology is expected to improve diagnostic performance by increasing accuracy and simplifying personalized decision-making. While this technology ha...

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Detalles Bibliográficos
Autores principales: Goisauf, Melanie, Cano Abadía, Mónica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9329694/
https://www.ncbi.nlm.nih.gov/pubmed/35910490
http://dx.doi.org/10.3389/fdata.2022.850383
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author Goisauf, Melanie
Cano Abadía, Mónica
author_facet Goisauf, Melanie
Cano Abadía, Mónica
author_sort Goisauf, Melanie
collection PubMed
description Artificial intelligence (AI) is being applied in medicine to improve healthcare and advance health equity. The application of AI-based technologies in radiology is expected to improve diagnostic performance by increasing accuracy and simplifying personalized decision-making. While this technology has the potential to improve health services, many ethical and societal implications need to be carefully considered to avoid harmful consequences for individuals and groups, especially for the most vulnerable populations. Therefore, several questions are raised, including (1) what types of ethical issues are raised by the use of AI in medicine and biomedical research, and (2) how are these issues being tackled in radiology, especially in the case of breast cancer? To answer these questions, a systematic review of the academic literature was conducted. Searches were performed in five electronic databases to identify peer-reviewed articles published since 2017 on the topic of the ethics of AI in radiology. The review results show that the discourse has mainly addressed expectations and challenges associated with medical AI, and in particular bias and black box issues, and that various guiding principles have been suggested to ensure ethical AI. We found that several ethical and societal implications of AI use remain underexplored, and more attention needs to be paid to addressing potential discriminatory effects and injustices. We conclude with a critical reflection on these issues and the identified gaps in the discourse from a philosophical and STS perspective, underlining the need to integrate a social science perspective in AI developments in radiology in the future.
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spelling pubmed-93296942022-07-29 Ethics of AI in Radiology: A Review of Ethical and Societal Implications Goisauf, Melanie Cano Abadía, Mónica Front Big Data Big Data Artificial intelligence (AI) is being applied in medicine to improve healthcare and advance health equity. The application of AI-based technologies in radiology is expected to improve diagnostic performance by increasing accuracy and simplifying personalized decision-making. While this technology has the potential to improve health services, many ethical and societal implications need to be carefully considered to avoid harmful consequences for individuals and groups, especially for the most vulnerable populations. Therefore, several questions are raised, including (1) what types of ethical issues are raised by the use of AI in medicine and biomedical research, and (2) how are these issues being tackled in radiology, especially in the case of breast cancer? To answer these questions, a systematic review of the academic literature was conducted. Searches were performed in five electronic databases to identify peer-reviewed articles published since 2017 on the topic of the ethics of AI in radiology. The review results show that the discourse has mainly addressed expectations and challenges associated with medical AI, and in particular bias and black box issues, and that various guiding principles have been suggested to ensure ethical AI. We found that several ethical and societal implications of AI use remain underexplored, and more attention needs to be paid to addressing potential discriminatory effects and injustices. We conclude with a critical reflection on these issues and the identified gaps in the discourse from a philosophical and STS perspective, underlining the need to integrate a social science perspective in AI developments in radiology in the future. Frontiers Media S.A. 2022-07-14 /pmc/articles/PMC9329694/ /pubmed/35910490 http://dx.doi.org/10.3389/fdata.2022.850383 Text en Copyright © 2022 Goisauf and Cano Abadía. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Goisauf, Melanie
Cano Abadía, Mónica
Ethics of AI in Radiology: A Review of Ethical and Societal Implications
title Ethics of AI in Radiology: A Review of Ethical and Societal Implications
title_full Ethics of AI in Radiology: A Review of Ethical and Societal Implications
title_fullStr Ethics of AI in Radiology: A Review of Ethical and Societal Implications
title_full_unstemmed Ethics of AI in Radiology: A Review of Ethical and Societal Implications
title_short Ethics of AI in Radiology: A Review of Ethical and Societal Implications
title_sort ethics of ai in radiology: a review of ethical and societal implications
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9329694/
https://www.ncbi.nlm.nih.gov/pubmed/35910490
http://dx.doi.org/10.3389/fdata.2022.850383
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