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Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey

BACKGROUND: Artificial intelligence (AI) needs to be accepted and understood by physicians and medical students, but few have systematically assessed their attitudes. We investigated clinical AI acceptance among physicians and medical students around the world to provide implementation guidance. MAT...

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Autores principales: Chen, Mingyang, Zhang, Bo, Cai, Ziting, Seery, Samuel, Gonzalez, Maria J., Ali, Nasra M., Ren, Ran, Qiao, Youlin, Xue, Peng, Jiang, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9472134/
https://www.ncbi.nlm.nih.gov/pubmed/36117979
http://dx.doi.org/10.3389/fmed.2022.990604
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author Chen, Mingyang
Zhang, Bo
Cai, Ziting
Seery, Samuel
Gonzalez, Maria J.
Ali, Nasra M.
Ren, Ran
Qiao, Youlin
Xue, Peng
Jiang, Yu
author_facet Chen, Mingyang
Zhang, Bo
Cai, Ziting
Seery, Samuel
Gonzalez, Maria J.
Ali, Nasra M.
Ren, Ran
Qiao, Youlin
Xue, Peng
Jiang, Yu
author_sort Chen, Mingyang
collection PubMed
description BACKGROUND: Artificial intelligence (AI) needs to be accepted and understood by physicians and medical students, but few have systematically assessed their attitudes. We investigated clinical AI acceptance among physicians and medical students around the world to provide implementation guidance. MATERIALS AND METHODS: We conducted a two-stage study, involving a foundational systematic review of physician and medical student acceptance of clinical AI. This enabled us to design a suitable web-based questionnaire which was then distributed among practitioners and trainees around the world. RESULTS: Sixty studies were included in this systematic review, and 758 respondents from 39 countries completed the online questionnaire. Five (62.50%) of eight studies reported 65% or higher awareness regarding the application of clinical AI. Although, only 10–30% had actually used AI and 26 (74.28%) of 35 studies suggested there was a lack of AI knowledge. Our questionnaire uncovered 38% awareness rate and 20% utility rate of clinical AI, although 53% lacked basic knowledge of clinical AI. Forty-five studies mentioned attitudes toward clinical AI, and over 60% from 38 (84.44%) studies were positive about AI, although they were also concerned about the potential for unpredictable, incorrect results. Seventy-seven percent were optimistic about the prospect of clinical AI. The support rate for the statement that AI could replace physicians ranged from 6 to 78% across 40 studies which mentioned this topic. Five studies recommended that efforts should be made to increase collaboration. Our questionnaire showed 68% disagreed that AI would become a surrogate physician, but believed it should assist in clinical decision-making. Participants with different identities, experience and from different countries hold similar but subtly different attitudes. CONCLUSION: Most physicians and medical students appear aware of the increasing application of clinical AI, but lack practical experience and related knowledge. Overall, participants have positive but reserved attitudes about AI. In spite of the mixed opinions around clinical AI becoming a surrogate physician, there was a consensus that collaborations between the two should be strengthened. Further education should be conducted to alleviate anxieties associated with change and adopting new technologies.
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spelling pubmed-94721342022-09-15 Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey Chen, Mingyang Zhang, Bo Cai, Ziting Seery, Samuel Gonzalez, Maria J. Ali, Nasra M. Ren, Ran Qiao, Youlin Xue, Peng Jiang, Yu Front Med (Lausanne) Medicine BACKGROUND: Artificial intelligence (AI) needs to be accepted and understood by physicians and medical students, but few have systematically assessed their attitudes. We investigated clinical AI acceptance among physicians and medical students around the world to provide implementation guidance. MATERIALS AND METHODS: We conducted a two-stage study, involving a foundational systematic review of physician and medical student acceptance of clinical AI. This enabled us to design a suitable web-based questionnaire which was then distributed among practitioners and trainees around the world. RESULTS: Sixty studies were included in this systematic review, and 758 respondents from 39 countries completed the online questionnaire. Five (62.50%) of eight studies reported 65% or higher awareness regarding the application of clinical AI. Although, only 10–30% had actually used AI and 26 (74.28%) of 35 studies suggested there was a lack of AI knowledge. Our questionnaire uncovered 38% awareness rate and 20% utility rate of clinical AI, although 53% lacked basic knowledge of clinical AI. Forty-five studies mentioned attitudes toward clinical AI, and over 60% from 38 (84.44%) studies were positive about AI, although they were also concerned about the potential for unpredictable, incorrect results. Seventy-seven percent were optimistic about the prospect of clinical AI. The support rate for the statement that AI could replace physicians ranged from 6 to 78% across 40 studies which mentioned this topic. Five studies recommended that efforts should be made to increase collaboration. Our questionnaire showed 68% disagreed that AI would become a surrogate physician, but believed it should assist in clinical decision-making. Participants with different identities, experience and from different countries hold similar but subtly different attitudes. CONCLUSION: Most physicians and medical students appear aware of the increasing application of clinical AI, but lack practical experience and related knowledge. Overall, participants have positive but reserved attitudes about AI. In spite of the mixed opinions around clinical AI becoming a surrogate physician, there was a consensus that collaborations between the two should be strengthened. Further education should be conducted to alleviate anxieties associated with change and adopting new technologies. Frontiers Media S.A. 2022-08-31 /pmc/articles/PMC9472134/ /pubmed/36117979 http://dx.doi.org/10.3389/fmed.2022.990604 Text en Copyright © 2022 Chen, Zhang, Cai, Seery, Gonzalez, Ali, Ren, Qiao, Xue and Jiang. 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 Medicine
Chen, Mingyang
Zhang, Bo
Cai, Ziting
Seery, Samuel
Gonzalez, Maria J.
Ali, Nasra M.
Ren, Ran
Qiao, Youlin
Xue, Peng
Jiang, Yu
Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey
title Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey
title_full Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey
title_fullStr Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey
title_full_unstemmed Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey
title_short Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey
title_sort acceptance of clinical artificial intelligence among physicians and medical students: a systematic review with cross-sectional survey
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9472134/
https://www.ncbi.nlm.nih.gov/pubmed/36117979
http://dx.doi.org/10.3389/fmed.2022.990604
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