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Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise
Introduction : Artificial Intelligence in Medicine (AIM) research is now 50 years old, having made great progress that has tracked the corresponding evolution of computer science, hardware technology, communications, and biomedicine. Characterized as being in its “adolescence” at an international me...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697517/ https://www.ncbi.nlm.nih.gov/pubmed/31022745 http://dx.doi.org/10.1055/s-0039-1677891 |
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author | Shortliffe, Edward H. |
author_facet | Shortliffe, Edward H. |
author_sort | Shortliffe, Edward H. |
collection | PubMed |
description | Introduction : Artificial Intelligence in Medicine (AIM) research is now 50 years old, having made great progress that has tracked the corresponding evolution of computer science, hardware technology, communications, and biomedicine. Characterized as being in its “adolescence” at an international meeting in 1991, and as “coming of age” at another meeting in 2007, the AIM field is now more visible and influential than ever before, paralleling the enthusiasm and accomplishments of artificial intelligence (AI) more generally. Objectives : This article summarizes some of that AIM history, providing an update on the status of the field as it enters its second half-century. It acknowledges the failure of AI, including AIM, to live up to early predictions of its likely capabilities and impact. Methods : The paper reviews and assesses the early history of the AIM field, referring to the conclusions of papers based on the meetings in 1991 and 2007, and analyzing the subsequent evolution of AIM. Conclusion : We must be cautious in assessing the speed at which further progress will be made, despite today’s wild predictions in the press and large investments by industry, including in health care. The inherent complexity of medicine and of clinical care necessitates that we address issues of usability, workflow, transparency, safety, and formal clinical trials. These requirements contribute to an ongoing research agenda that means academic AIM research will continue to be vibrant while having new opportunities for more interactions with industry. |
format | Online Article Text |
id | pubmed-6697517 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-66975172019-08-19 Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise Shortliffe, Edward H. Yearb Med Inform Introduction : Artificial Intelligence in Medicine (AIM) research is now 50 years old, having made great progress that has tracked the corresponding evolution of computer science, hardware technology, communications, and biomedicine. Characterized as being in its “adolescence” at an international meeting in 1991, and as “coming of age” at another meeting in 2007, the AIM field is now more visible and influential than ever before, paralleling the enthusiasm and accomplishments of artificial intelligence (AI) more generally. Objectives : This article summarizes some of that AIM history, providing an update on the status of the field as it enters its second half-century. It acknowledges the failure of AI, including AIM, to live up to early predictions of its likely capabilities and impact. Methods : The paper reviews and assesses the early history of the AIM field, referring to the conclusions of papers based on the meetings in 1991 and 2007, and analyzing the subsequent evolution of AIM. Conclusion : We must be cautious in assessing the speed at which further progress will be made, despite today’s wild predictions in the press and large investments by industry, including in health care. The inherent complexity of medicine and of clinical care necessitates that we address issues of usability, workflow, transparency, safety, and formal clinical trials. These requirements contribute to an ongoing research agenda that means academic AIM research will continue to be vibrant while having new opportunities for more interactions with industry. Georg Thieme Verlag KG 2019-08 2019-04-25 /pmc/articles/PMC6697517/ /pubmed/31022745 http://dx.doi.org/10.1055/s-0039-1677891 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Shortliffe, Edward H. Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise |
title | Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise |
title_full | Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise |
title_fullStr | Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise |
title_full_unstemmed | Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise |
title_short | Artificial Intelligence in Medicine: Weighing the Accomplishments, Hype, and Promise |
title_sort | artificial intelligence in medicine: weighing the accomplishments, hype, and promise |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697517/ https://www.ncbi.nlm.nih.gov/pubmed/31022745 http://dx.doi.org/10.1055/s-0039-1677891 |
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