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Teaching artificial intelligence as a fundamental toolset of medicine
Artificial intelligence (AI) is transforming the practice of medicine. Systems assessing chest radiographs, pathology slides, and early warning systems embedded in electronic health records (EHRs) are becoming ubiquitous in medical practice. Despite this, medical students have minimal exposure to th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797941/ https://www.ncbi.nlm.nih.gov/pubmed/36543111 http://dx.doi.org/10.1016/j.xcrm.2022.100824 |
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author | Ötleş, Erkin James, Cornelius A. Lomis, Kimberly D. Woolliscroft, James O. |
author_facet | Ötleş, Erkin James, Cornelius A. Lomis, Kimberly D. Woolliscroft, James O. |
author_sort | Ötleş, Erkin |
collection | PubMed |
description | Artificial intelligence (AI) is transforming the practice of medicine. Systems assessing chest radiographs, pathology slides, and early warning systems embedded in electronic health records (EHRs) are becoming ubiquitous in medical practice. Despite this, medical students have minimal exposure to the concepts necessary to utilize and evaluate AI systems, leaving them under prepared for future clinical practice. We must work quickly to bolster undergraduate medical education around AI to remedy this. In this commentary, we propose that medical educators treat AI as a critical component of medical practice that is introduced early and integrated with the other core components of medical school curricula. Equipping graduating medical students with this knowledge will ensure they have the skills to solve challenges arising at the confluence of AI and medicine. |
format | Online Article Text |
id | pubmed-9797941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97979412022-12-30 Teaching artificial intelligence as a fundamental toolset of medicine Ötleş, Erkin James, Cornelius A. Lomis, Kimberly D. Woolliscroft, James O. Cell Rep Med Commentary Artificial intelligence (AI) is transforming the practice of medicine. Systems assessing chest radiographs, pathology slides, and early warning systems embedded in electronic health records (EHRs) are becoming ubiquitous in medical practice. Despite this, medical students have minimal exposure to the concepts necessary to utilize and evaluate AI systems, leaving them under prepared for future clinical practice. We must work quickly to bolster undergraduate medical education around AI to remedy this. In this commentary, we propose that medical educators treat AI as a critical component of medical practice that is introduced early and integrated with the other core components of medical school curricula. Equipping graduating medical students with this knowledge will ensure they have the skills to solve challenges arising at the confluence of AI and medicine. Elsevier 2022-12-20 /pmc/articles/PMC9797941/ /pubmed/36543111 http://dx.doi.org/10.1016/j.xcrm.2022.100824 Text en © 2022 The Author(s) https://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 | Commentary Ötleş, Erkin James, Cornelius A. Lomis, Kimberly D. Woolliscroft, James O. Teaching artificial intelligence as a fundamental toolset of medicine |
title | Teaching artificial intelligence as a fundamental toolset of medicine |
title_full | Teaching artificial intelligence as a fundamental toolset of medicine |
title_fullStr | Teaching artificial intelligence as a fundamental toolset of medicine |
title_full_unstemmed | Teaching artificial intelligence as a fundamental toolset of medicine |
title_short | Teaching artificial intelligence as a fundamental toolset of medicine |
title_sort | teaching artificial intelligence as a fundamental toolset of medicine |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797941/ https://www.ncbi.nlm.nih.gov/pubmed/36543111 http://dx.doi.org/10.1016/j.xcrm.2022.100824 |
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