Artificial General Intelligence for Medical Imaging

• URL: http://arxiv.org/abs/2306.05480v2
• Date: Mon, 3 Jul 2023 01:52:58 GMT
• Title: Artificial General Intelligence for Medical Imaging
• Authors: Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkun Yan, Quanzheng Li, Wei Liu, Tianming Liu, and Dinggang Shen
• Abstract summary: In this review, we explore the potential applications of Artificial General Intelligence (AGI) models in healthcare. We emphasize the importance of integrating clinical expertise, domain knowledge, and multimodal capabilities into AGI models.
• Score: 62.116506368045606
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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