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：本综述探讨了人工通用智能（AGI）模型在医疗健康中的潜在应用，重点关注基础大语言模型（LLMs）、大型视觉模型和大型多模态模型。我们强调了将临床专业知识、领域知识与多模态能力整合至AGI模型的重要性。此外，我们提出了指导医疗AGI模型开发与部署的关键路线图。贯穿全文，我们围绕在医学领域部署大规模AGI模型所面临的潜在挑战与陷阱提供了批判性视角。本综述旨在为AGI在医学影像、医疗健康及更广泛领域的未来影响提供深入见解。