将生成式人工智能（GenAI）应用于临床医疗保健所面临的挑战。
Challenges for implementing generative artificial intelligence (GenAI) into clinical healthcare.
作者信息
Roberts Lynden J, Jayasena Rajiv, Khanna Sankalp, Arnott Leslie, Lane Paul, Bain Chris
机构信息
Department of Clinical Informatics, Monash Health, Melbourne, Victoria, Australia.
Australian E-Health Research Centre, CSIRO, Melbourne, Victoria, Australia.
出版信息
Intern Med J. 2025 Jul;55(7):1063-1069. doi: 10.1111/imj.70035. Epub 2025 Mar 26.
Generative artificial intelligence (GenAI) is a form of deep learning AI based on inference that offers significant potential in healthcare. It has versatile capabilities: GenAI excels in complex human language communication, synthesising information from large and diverse datasets and performing broad, complex tasks reliably. Other important capabilities include scalability, 'always on' and cost effectiveness. Taken together, GenAI technology appears to possess considerable potential for healthcare. However, the implementation poses several challenges, including technological problems, regulatory considerations, workforce impact and building trust. Using evidence and expert opinion to explore these issues, the review aims to inform clinical experts about this rapidly evolving field.
生成式人工智能（GenAI）是一种基于推理的深度学习人工智能形式，在医疗保健领域具有巨大潜力。它具有多种功能：GenAI在复杂的人类语言交流方面表现出色，能够从大量多样的数据集中合成信息，并可靠地执行广泛而复杂的任务。其他重要功能包括可扩展性、“始终在线”和成本效益。总体而言，GenAI技术在医疗保健领域似乎具有相当大的潜力。然而，其实施带来了若干挑战，包括技术问题、监管考量、对劳动力的影响以及建立信任。本综述利用证据和专家意见来探讨这些问题，旨在让临床专家了解这一快速发展的领域。
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