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直面人工智能对传染病工作队伍的冲击:这对我们意味着什么以及我们能做些什么。

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

作者信息

Langford Bradley J, Branch-Elliman Westyn, Nori Priya, Marra Alexandre R, Bearman Gonzalo

机构信息

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

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

出版信息

Open Forum Infect Dis. 2024 Jan 31;11(3):ofae053. doi: 10.1093/ofid/ofae053. eCollection 2024 Mar.

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.

摘要

随着人工智能(AI)的迅速发展,传染病(ID)领域既面临创新也面临变革。AI及其子领域,包括机器学习、深度学习和大语言模型,可以支持传染病临床医生的决策并简化其工作流程。AI模型可能有助于确保更早地发现疾病、提供更个性化的经验性治疗建议,以及分配人力资源以支持更高效率的抗菌药物管理和感染预防策略。AI不太可能取代传染病专家的角色,反而可能增强其作用。然而,需要仔细解决并减轻其局限性,以确保安全有效地实施。传染病专家可以通过参与培训和教育、确定AI的用例以帮助改善患者护理、设计、验证和评估算法,以及继续倡导其在患者护理中的重要作用,来参与AI的实施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a538/10906702/81ea8dadec44/ofae053f1.jpg

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