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Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches
AI-based prediction models demonstrate equal or surpassing performance compared to experienced physicians in various research settings. However, only a few have made it into clinical practice. Further, there is no standardized protocol for integrating AI-based physician support systems into the dail...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404285/ https://www.ncbi.nlm.nih.gov/pubmed/37543707 http://dx.doi.org/10.1038/s41746-023-00889-6 |
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author | Mittermaier, Mirja Raza, Marium Kvedar, Joseph C. |
author_facet | Mittermaier, Mirja Raza, Marium Kvedar, Joseph C. |
author_sort | Mittermaier, Mirja |
collection | PubMed |
description | AI-based prediction models demonstrate equal or surpassing performance compared to experienced physicians in various research settings. However, only a few have made it into clinical practice. Further, there is no standardized protocol for integrating AI-based physician support systems into the daily clinical routine to improve healthcare delivery. Generally, AI/physician collaboration strategies have not been extensively investigated. A recent study compared four potential strategies for AI model deployment and physician collaboration to investigate the performance of an AI model trained to identify signs of acute respiratory distress syndrome (ARDS) on chest X-ray images. Here we discuss strategies and challenges with AI/physician collaboration when AI-based decision support systems are implemented in the clinical routine. |
format | Online Article Text |
id | pubmed-10404285 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104042852023-08-07 Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches Mittermaier, Mirja Raza, Marium Kvedar, Joseph C. NPJ Digit Med Editorial AI-based prediction models demonstrate equal or surpassing performance compared to experienced physicians in various research settings. However, only a few have made it into clinical practice. Further, there is no standardized protocol for integrating AI-based physician support systems into the daily clinical routine to improve healthcare delivery. Generally, AI/physician collaboration strategies have not been extensively investigated. A recent study compared four potential strategies for AI model deployment and physician collaboration to investigate the performance of an AI model trained to identify signs of acute respiratory distress syndrome (ARDS) on chest X-ray images. Here we discuss strategies and challenges with AI/physician collaboration when AI-based decision support systems are implemented in the clinical routine. Nature Publishing Group UK 2023-08-05 /pmc/articles/PMC10404285/ /pubmed/37543707 http://dx.doi.org/10.1038/s41746-023-00889-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Editorial Mittermaier, Mirja Raza, Marium Kvedar, Joseph C. Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches |
title | Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches |
title_full | Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches |
title_fullStr | Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches |
title_full_unstemmed | Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches |
title_short | Collaborative strategies for deploying AI-based physician decision support systems: challenges and deployment approaches |
title_sort | collaborative strategies for deploying ai-based physician decision support systems: challenges and deployment approaches |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10404285/ https://www.ncbi.nlm.nih.gov/pubmed/37543707 http://dx.doi.org/10.1038/s41746-023-00889-6 |
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