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Artificial intelligence in medical education: a cross-sectional needs assessment

BACKGROUND: As the information age wanes, enabling the prevalence of the artificial intelligence age; expectations, responsibilities, and job definitions need to be redefined for those who provide services in healthcare. This study examined the perceptions of future physicians on the possible influe...

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Autores principales: Civaner, M. Murat, Uncu, Yeşim, Bulut, Filiz, Chalil, Esra Giounous, Tatli, Abdülhamit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646274/
https://www.ncbi.nlm.nih.gov/pubmed/36352431
http://dx.doi.org/10.1186/s12909-022-03852-3
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author Civaner, M. Murat
Uncu, Yeşim
Bulut, Filiz
Chalil, Esra Giounous
Tatli, Abdülhamit
author_facet Civaner, M. Murat
Uncu, Yeşim
Bulut, Filiz
Chalil, Esra Giounous
Tatli, Abdülhamit
author_sort Civaner, M. Murat
collection PubMed
description BACKGROUND: As the information age wanes, enabling the prevalence of the artificial intelligence age; expectations, responsibilities, and job definitions need to be redefined for those who provide services in healthcare. This study examined the perceptions of future physicians on the possible influences of artificial intelligence on medicine, and to determine the needs that might be helpful for curriculum restructuring. METHODS: A cross-sectional multi-centre study was conducted among medical students country-wide, where 3018 medical students participated. The instrument of the study was an online survey that was designed and distributed via a web-based service. RESULTS: Most of the medical students perceived artificial intelligence as an assistive technology that could facilitate physicians’ access to information (85.8%) and patients to healthcare (76.7%), and reduce errors (70.5%). However, half of the participants were worried about the possible reduction in the services of physicians, which could lead to unemployment (44.9%). Furthermore, it was agreed that using artificial intelligence in medicine could devalue the medical profession (58.6%), damage trust (45.5%), and negatively affect patient-physician relationships (42.7%). Moreover, nearly half of the participants affirmed that they could protect their professional confidentiality when using artificial intelligence applications (44.7%); whereas, 16.1% argued that artificial intelligence in medicine might cause violations of professional confidentiality. Of all the participants, only 6.0% stated that they were competent enough to inform patients about the features and risks of artificial intelligence. They further expressed that their educational gaps regarding their need for “knowledge and skills related to artificial intelligence applications” (96.2%), “applications for reducing medical errors” (95.8%), and “training to prevent and solve ethical problems that might arise as a result of using artificial intelligence applications” (93.8%). CONCLUSIONS: The participants expressed a need for an update on the medical curriculum, according to necessities in transforming healthcare driven by artificial intelligence. The update should revolve around equipping future physicians with the knowledge and skills to effectively use artificial intelligence applications and ensure that professional values and rights are protected.
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spelling pubmed-96462742022-11-14 Artificial intelligence in medical education: a cross-sectional needs assessment Civaner, M. Murat Uncu, Yeşim Bulut, Filiz Chalil, Esra Giounous Tatli, Abdülhamit BMC Med Educ Research BACKGROUND: As the information age wanes, enabling the prevalence of the artificial intelligence age; expectations, responsibilities, and job definitions need to be redefined for those who provide services in healthcare. This study examined the perceptions of future physicians on the possible influences of artificial intelligence on medicine, and to determine the needs that might be helpful for curriculum restructuring. METHODS: A cross-sectional multi-centre study was conducted among medical students country-wide, where 3018 medical students participated. The instrument of the study was an online survey that was designed and distributed via a web-based service. RESULTS: Most of the medical students perceived artificial intelligence as an assistive technology that could facilitate physicians’ access to information (85.8%) and patients to healthcare (76.7%), and reduce errors (70.5%). However, half of the participants were worried about the possible reduction in the services of physicians, which could lead to unemployment (44.9%). Furthermore, it was agreed that using artificial intelligence in medicine could devalue the medical profession (58.6%), damage trust (45.5%), and negatively affect patient-physician relationships (42.7%). Moreover, nearly half of the participants affirmed that they could protect their professional confidentiality when using artificial intelligence applications (44.7%); whereas, 16.1% argued that artificial intelligence in medicine might cause violations of professional confidentiality. Of all the participants, only 6.0% stated that they were competent enough to inform patients about the features and risks of artificial intelligence. They further expressed that their educational gaps regarding their need for “knowledge and skills related to artificial intelligence applications” (96.2%), “applications for reducing medical errors” (95.8%), and “training to prevent and solve ethical problems that might arise as a result of using artificial intelligence applications” (93.8%). CONCLUSIONS: The participants expressed a need for an update on the medical curriculum, according to necessities in transforming healthcare driven by artificial intelligence. The update should revolve around equipping future physicians with the knowledge and skills to effectively use artificial intelligence applications and ensure that professional values and rights are protected. BioMed Central 2022-11-09 /pmc/articles/PMC9646274/ /pubmed/36352431 http://dx.doi.org/10.1186/s12909-022-03852-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Civaner, M. Murat
Uncu, Yeşim
Bulut, Filiz
Chalil, Esra Giounous
Tatli, Abdülhamit
Artificial intelligence in medical education: a cross-sectional needs assessment
title Artificial intelligence in medical education: a cross-sectional needs assessment
title_full Artificial intelligence in medical education: a cross-sectional needs assessment
title_fullStr Artificial intelligence in medical education: a cross-sectional needs assessment
title_full_unstemmed Artificial intelligence in medical education: a cross-sectional needs assessment
title_short Artificial intelligence in medical education: a cross-sectional needs assessment
title_sort artificial intelligence in medical education: a cross-sectional needs assessment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646274/
https://www.ncbi.nlm.nih.gov/pubmed/36352431
http://dx.doi.org/10.1186/s12909-022-03852-3
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