Healthcare systems worldwide face persistent challenges in efficiency, accessibility, and personalization. Powered by modern AI technologies such as multimodal large language models and world models, Embodied AI (EmAI) represents a transformative frontier, offering enhanced autonomy and the ability to interact with the physical world to address these challenges. As an interdisciplinary and rapidly evolving research domain, "EmAI in healthcare" spans diverse fields such as algorithms, robotics, and biomedicine. This complexity underscores the importance of timely reviews and analyses to track advancements, address challenges, and foster cross-disciplinary collaboration. In this paper, we provide a comprehensive overview of the "brain" of EmAI for healthcare, wherein we introduce foundational AI algorithms for perception, actuation, planning, and memory, and focus on presenting the healthcare applications spanning clinical interventions, daily care & companionship, infrastructure support, and biomedical research. Despite its promise, the development of EmAI for healthcare is hindered by critical challenges such as safety concerns, gaps between simulation platforms and real-world applications, the absence of standardized benchmarks, and uneven progress across interdisciplinary domains. We discuss the technical barriers and explore ethical considerations, offering a forward-looking perspective on the future of EmAI in healthcare. A hierarchical framework of intelligent levels for EmAI systems is also introduced to guide further development. By providing systematic insights, this work aims to inspire innovation and practical applications, paving the way for a new era of intelligent, patient-centered healthcare.

翻译：全球医疗保健系统在效率、可及性和个性化方面持续面临挑战。由多模态大语言模型与世界模型等现代人工智能技术驱动的具身人工智能（EmAI）代表着一个变革性的前沿领域，它通过增强自主性和与现实世界交互的能力来应对这些挑战。作为一个跨学科且快速发展的研究领域，“医疗保健领域的具身人工智能”横跨算法、机器人和生物医学等多个领域。这种复杂性凸显了及时进行综述与分析以追踪进展、应对挑战并促进跨学科合作的重要性。本文对医疗保健领域具身人工智能的“大脑”进行了全面概述，介绍了感知、驱动、规划与记忆的基础性AI算法，并重点呈现了涵盖临床干预、日常护理与陪伴、基础设施支持以及生物医学研究的医疗保健应用。尽管前景广阔，医疗保健领域具身人工智能的发展仍受制于诸多关键挑战，例如安全问题、仿真平台与现实应用之间的差距、标准化基准的缺失以及跨学科领域进展不均衡等。我们讨论了技术障碍，探讨了伦理考量，并对医疗保健领域具身人工智能的未来提供了前瞻性视角。本文还引入了一个具身人工智能系统智能水平的分层框架以指导未来发展。通过提供系统性的见解，本工作旨在激发创新与实际应用，为迈向以患者为中心的智能医疗新时代铺平道路。