Confronting the Disruption of the Infectious Diseases Workforce by Artificial Intelligence: What This Means for Us and What We Can Do About It

Author:

Langford Bradley J12ORCID,Branch-Elliman Westyn345ORCID,Nori Priya6,Marra Alexandre R78,Bearman Gonzalo9

Affiliation:

1. Dalla Lana School of Public Health, University of Toronto , Toronto, Ontario , Canada

2. Hotel Dieu Shaver Health and Rehabilitation Centre , Department of Pharmacy, St Catharines, Ontario , Canada

3. Department of Medicine, Section of Infectious Diseases, Veterans Affairs Boston Healthcare System , Boston, Massachusetts , USA

4. National Artificial Intelligence Institute, Department of Veterans Affairs , Washington, District of Columbia , USA

5. Harvard Medical School , Boston, Massachusetts , USA

6. Division of Infectious Diseases, Department of Medicine, Montefiore Health System, Albert Einstein College of Medicine , Bronx, New York , USA

7. Instituto Israelita de Ensino e Pesquisa Albert Einstein, Hospital Israelita Albert Einstein , São Paulo , Brazil

8. Department of Internal Medicine, University of Iowa Carver College of Medicine , Iowa City, Iowa , USA

9. Division of Infectious Diseases, Virginia Commonwealth University Health, Virginia Commonwealth University , Richmond, Virginia , USA

Abstract

Abstract With the rapid advancement of artificial intelligence (AI), the field of infectious diseases (ID) faces both innovation and disruption. AI and its subfields including machine learning, deep learning, and large language models can support ID clinicians’ decision making and streamline their workflow. AI models may help ensure earlier detection of disease, more personalized empiric treatment recommendations, and allocation of human resources to support higher-yield antimicrobial stewardship and infection prevention strategies. AI is unlikely to replace the role of ID experts, but could instead augment it. However, its limitations will need to be carefully addressed and mitigated to ensure safe and effective implementation. ID experts can be engaged in AI implementation by participating in training and education, identifying use cases for AI to help improve patient care, designing, validating and evaluating algorithms, and continuing to advocate for their vital role in patient care.

Publisher

Oxford University Press (OUP)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3