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Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?
There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and prac...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Elsevier
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133460/ https://www.ncbi.nlm.nih.gov/pubmed/35584620 http://dx.doi.org/10.1016/j.xcrm.2022.100622 |
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author | London, Alex John |
author_facet | London, Alex John |
author_sort | London, Alex John |
collection | PubMed |
description | There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their development. This perspective elaborates on some of these structural challenges and provides recommendations to address potential shortcomings. |
format | Online Article Text |
id | pubmed-9133460 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-91334602022-05-27 Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? London, Alex John Cell Rep Med Perspective There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their development. This perspective elaborates on some of these structural challenges and provides recommendations to address potential shortcomings. Elsevier 2022-04-27 /pmc/articles/PMC9133460/ /pubmed/35584620 http://dx.doi.org/10.1016/j.xcrm.2022.100622 Text en © 2022 The Author 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 | Perspective London, Alex John Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? |
title | Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? |
title_full | Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? |
title_fullStr | Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? |
title_full_unstemmed | Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? |
title_short | Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care? |
title_sort | artificial intelligence in medicine: overcoming or recapitulating structural challenges to improving patient care? |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133460/ https://www.ncbi.nlm.nih.gov/pubmed/35584620 http://dx.doi.org/10.1016/j.xcrm.2022.100622 |
work_keys_str_mv | AT londonalexjohn artificialintelligenceinmedicineovercomingorrecapitulatingstructuralchallengestoimprovingpatientcare |