In this review, we explore the potential applications of Artificial General Intelligence (AGI) models in healthcare, focusing on foundational Large Language Models (LLMs), Large Vision Models, and Large Multimodal Models. We emphasize the importance of integrating clinical expertise, domain knowledge, and multimodal capabilities into AGI models. In addition, we lay out key roadmaps that guide the development and deployment of healthcare AGI models. Throughout the review, we provide critical perspectives on the potential challenges and pitfalls associated with deploying large-scale AGI models in the medical field. This comprehensive review aims to offer insights into the future implications of AGI in medical imaging, healthcare and beyond.

翻译：本文综述了通用人工智能（AGI）模型在医疗健康领域的潜在应用，重点聚焦基础大语言模型（LLM）、大型视觉模型及大型多模态模型。我们强调了将临床专业知识、领域知识及多模态能力整合至AGI模型中的重要性。此外，我们提出了指导医疗健康AGI模型开发与部署的关键路线图。本综述始终围绕在医学领域部署大规模AGI模型所伴随的潜在挑战与陷阱展开批判性讨论。这一系统性回顾旨在为AGI在医学影像、医疗健康及其更广泛领域的未来影响提供深刻见解。