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The integration of large language models (LLMs) and generative artificial intelligence (AI) in health care holds the potential to transform the practice of medicine, the work and experiences of health care providers, and the health and well-being of patients. Generative AI can support clinical decision making and streamline workflows, promote patients and their support networks' engagement in care processes, and support clinical research.
However, successful and ethical implementation of generative AI requires careful consideration of the associated risks, particularly those concerning data privacy, bias, transparency, and infrastructure limitations.
Generative Artificial Intelligence in Health and Medicine: Opportunities and Responsibilities for Transformative Innovation explores the transformative potential of generative AI in health care, with a focus on its applications in clinical decision making, administrative efficiency, and patient engagement.
Table of Contents
Front Matter 1 Introduction 2 Opportunities and Early Evidence for Generative Artificial Intelligence in Health and Medicine 3 Risks of Generative Artificial Intelligence in Health and Medicine 4 Application Readiness Cadence 5 The Path Forward References Author Information Appendix: Rapid Field Development and Progress
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The integration of large language models (LLMs) and generative artificial intelligence (AI) in health care holds the potential to transform the practice of medicine, the work and experiences of health care providers, and the health and well-being of patients. Generative AI can support clinical decision making and streamline workflows, promote patients and their support networks' engagement in care processes, and support clinical research.
However, successful and ethical implementation of generative AI requires careful consideration of the associated risks, particularly those concerning data privacy, bias, transparency, and infrastructure limitations.
Generative Artificial Intelligence in Health and Medicine: Opportunities and Responsibilities for Transformative Innovation explores the transformative potential of generative AI in health care, with a focus on its applications in clinical decision making, administrative efficiency, and patient engagement.
Table of Contents
Front Matter 1 Introduction 2 Opportunities and Early Evidence for Generative Artificial Intelligence in Health and Medicine 3 Risks of Generative Artificial Intelligence in Health and Medicine 4 Application Readiness Cadence 5 The Path Forward References Author Information Appendix: Rapid Field Development and Progress