Ryan C Godwin, Avery Tung, Dan E Berkowitz, Ryan L Melvin
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Transforming Physiology and Healthcare through Foundation Models.
Recent developments in artificial intelligence (AI) may significantly alter physiological research and healthcare delivery. Whereas AI applications in medicine have historically been trained for specific tasks, recent technological advances have produced models trained on more diverse datasets with much higher parameter counts. These new, "foundation" models raise the possibility that more flexible AI tools can be applied to a wider set of healthcare tasks than in the past. This review describes how these newer models differ from conventional task-specific AI, which relies heavily on focused datasets and narrow, specific applications. By examining the integration of AI into diagnostic tools, personalized treatment strategies, biomedical research, and healthcare administration, we highlight how these newer models are revolutionizing predictive healthcare analytics and operational workflows. In addition, we address ethical and practical considerations associated with the use of foundation models by highlighting emerging trends, calling for changes to existing guidelines, and emphasizing the importance of aligning AI with clinical goals to ensure its responsible and effective use.
期刊介绍:
Physiology journal features meticulously crafted review articles penned by esteemed leaders in their respective fields. These articles undergo rigorous peer review and showcase the forefront of cutting-edge advances across various domains of physiology. Our Editorial Board, comprised of distinguished leaders in the broad spectrum of physiology, convenes annually to deliberate and recommend pioneering topics for review articles, as well as select the most suitable scientists to author these articles. Join us in exploring the forefront of physiological research and innovation.