Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

BACKGROUND:Due to the mechanical properties,unstable drug release,single function and other problems of pure hydrogel materials,in recent years,researchers have prepared a variety of metal organic frameworks-based hydrogel materials by introducing metal organic frameworks into hydrogel,and showed great potential in the field of soft and hard tissue regeneration. OBJECTIVE:To classify the metal organic frameworks-based hydrogel materials based on how metal organic frameworks enhance the properties of hydrogel and further summarize its recent research in the field of soft and hard tissue regeneration,in order to provide ideas and theoretical supports for the subsequent in-depth research on synthesis mechanism and clinical application of the composite material. METHODS:Using"metal organic frameworks,hydrogels,tissue engineering,tissue,bone regeneration,bone,wound"as English and Chinese search terms,we searched Web of Science,PubMed,CNKI,and Wanfang databases.The search period ranged from January 2000 to August 2023.By reading the titles and abstracts,the repetitive studies and unrelated literature of Chinese and English literature were excluded.After the literature quality evaluation,73 articles were included for review. RESULTS AND CONCLUSION:(1)Metal organic frameworks-based hydrogel materials effectively solve the problems of poor mechanical properties,unstable drug release and single function of pure hydrogel.(2)Metal organic frameworks enhance the capacity of repair and regeneration by strengthening the cross-linking of hydrogel,the drug delivery capacity of hydrogel and the multifunction of hydrogel.(3)In terms of hard tissue repair,it has shown good repair effects in animal models of diseases such as bone defects,osteoarthritis,and cartilage defects,suggesting potential application prospects in clinical repair.(4)In terms of soft tissue regeneration,it has the capacities of hemostasis,antibacterial,inflammatory state regulation,oxidative stress state regulation,promoting angiogenesis and other functions,effectively improving the microenvironment of various complex wounds and promoting soft tissue regeneration.(5)Although metal organic frameworks-based hydrogels have many excellent properties,they are still in the initial stage and there are some urgent problems to be solved in the process of clinical transformation,such as the cytotoxicity of metal organic frameworks and large-scale synthesis of metal organic frameworks.(6)With further research,metal organic frameworks-based hydrogels have broad application prospects in the field of soft and hard tissue repair.

This review summarizes the clinical data of one pediatric liver transplant recipient and two adult kidney transplant recipients with posterior reversible encephalopathy syndrome(PRES)at Tongji Hospital of Huazhong University of Science & Technology.The relevant clinical characteristics of recipients are discussed for providing reference for clinical diagnoses and treatments.