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Evaluating artificial intelligence in medicine: phases of clinical research
Increased scrutiny of artificial intelligence (AI) applications in healthcare highlights the need for real-world evaluations for effectiveness and unintended consequences. The complexity of healthcare, compounded by the user- and context-dependent nature of AI applications, calls for a multifaceted...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660958/ https://www.ncbi.nlm.nih.gov/pubmed/33215066 http://dx.doi.org/10.1093/jamiaopen/ooaa033 |
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author | Park, Yoonyoung Jackson, Gretchen Purcell Foreman, Morgan A Gruen, Daniel Hu, Jianying Das, Amar K |
author_facet | Park, Yoonyoung Jackson, Gretchen Purcell Foreman, Morgan A Gruen, Daniel Hu, Jianying Das, Amar K |
author_sort | Park, Yoonyoung |
collection | PubMed |
description | Increased scrutiny of artificial intelligence (AI) applications in healthcare highlights the need for real-world evaluations for effectiveness and unintended consequences. The complexity of healthcare, compounded by the user- and context-dependent nature of AI applications, calls for a multifaceted approach beyond traditional in silico evaluation of AI. We propose an interdisciplinary, phased research framework for evaluation of AI implementations in healthcare. We draw analogies to and highlight differences from the clinical trial phases for drugs and medical devices, and we present study design and methodological guidance for each stage. |
format | Online Article Text |
id | pubmed-7660958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76609582020-11-18 Evaluating artificial intelligence in medicine: phases of clinical research Park, Yoonyoung Jackson, Gretchen Purcell Foreman, Morgan A Gruen, Daniel Hu, Jianying Das, Amar K JAMIA Open Perspective Increased scrutiny of artificial intelligence (AI) applications in healthcare highlights the need for real-world evaluations for effectiveness and unintended consequences. The complexity of healthcare, compounded by the user- and context-dependent nature of AI applications, calls for a multifaceted approach beyond traditional in silico evaluation of AI. We propose an interdisciplinary, phased research framework for evaluation of AI implementations in healthcare. We draw analogies to and highlight differences from the clinical trial phases for drugs and medical devices, and we present study design and methodological guidance for each stage. Oxford University Press 2020-09-08 /pmc/articles/PMC7660958/ /pubmed/33215066 http://dx.doi.org/10.1093/jamiaopen/ooaa033 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Perspective Park, Yoonyoung Jackson, Gretchen Purcell Foreman, Morgan A Gruen, Daniel Hu, Jianying Das, Amar K Evaluating artificial intelligence in medicine: phases of clinical research |
title | Evaluating artificial intelligence in medicine: phases of clinical research |
title_full | Evaluating artificial intelligence in medicine: phases of clinical research |
title_fullStr | Evaluating artificial intelligence in medicine: phases of clinical research |
title_full_unstemmed | Evaluating artificial intelligence in medicine: phases of clinical research |
title_short | Evaluating artificial intelligence in medicine: phases of clinical research |
title_sort | evaluating artificial intelligence in medicine: phases of clinical research |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660958/ https://www.ncbi.nlm.nih.gov/pubmed/33215066 http://dx.doi.org/10.1093/jamiaopen/ooaa033 |
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