适应(眼睛)
医学
领域(数学分析)
医疗保健
工程伦理学
精密医学
病理
心理学
工程类
政治学
数学分析
数学
神经科学
法学
作者
Mert Karabacak,Konstantinos Margetis
出处
期刊:Cureus
[Cureus, Inc.]
日期:2023-05-21
被引量:56
摘要
Large language models (LLMs) have the potential to revolutionize the field of medicine by, among other applications, improving diagnostic accuracy and supporting clinical decision-making. However, the successful integration of LLMs in medicine requires addressing challenges and considerations specific to the medical domain. This viewpoint article provides a comprehensive overview of key aspects for the successful implementation of LLMs in medicine, including transfer learning, domain-specific fine-tuning, domain adaptation, reinforcement learning with expert input, dynamic training, interdisciplinary collaboration, education and training, evaluation metrics, clinical validation, ethical considerations, data privacy, and regulatory frameworks. By adopting a multifaceted approach and fostering interdisciplinary collaboration, LLMs can be developed, validated, and integrated into medical practice responsibly, effectively, and ethically, addressing the needs of various medical disciplines and diverse patient populations. Ultimately, this approach will ensure that LLMs enhance patient care and improve overall health outcomes for all.
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