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*

Neoantigens exhibit high immunogenic potential and confer a uniqueness to tumor cells, making them ideal targets for personalized cancer immunotherapy. Neoantigens originate from tumor-specific genetic alterations, abnormal viral infections, or other biological mechanisms, including atypical RNA splicing events and post-translational modifications (PTMs). These neoantigens are recognized as foreign by the immune system, eliciting an immune response that largely bypasses conventional mechanisms of central and peripheral tolerance. Advances in next-generation sequencing (NGS), mass spectrometry (MS), and artificial intelligence (AI) have greatly expedited the rapid detection and forecasting of neoantigens, markedly propelling the development of diverse immunotherapeutic strategies, including cancer vaccines, adoptive cell therapy, and antibody treatment. In this review, we comprehensively explore the discovery and characterization of neoantigens and their clinical use within promising immunotherapeutic frameworks. Additionally, we address the current landscape of neoantigen research, the intrinsic challenges of the field, and potential pathways for clinical application in cancer treatment.
Humans ; Neoplasms/therapy* ; Precision Medicine/methods* ; Immunotherapy/methods* ; Antigens, Neoplasm/genetics* ; Cancer Vaccines/immunology* ; High-Throughput Nucleotide Sequencing

With the rapid development of artificial intelligence, computational pathology has been seamlessly integrated into the entire clinical workflow, which encompasses diagnosis, treatment, prognosis, and biomarker discovery. This integration has significantly enhanced clinical accuracy and efficiency while reducing the workload for clinicians. Traditionally, research in this field has depended on the collection and labeling of large datasets for specific tasks, followed by the development of task-specific computational pathology models. However, this approach is labor intensive and does not scale efficiently for open-set identification or rare diseases. Given the diversity of clinical tasks, training individual models from scratch to address the whole spectrum of clinical tasks in the pathology workflow is impractical, which highlights the urgent need to transition from task-specific models to foundation models (FMs). In recent years, pathological FMs have proliferated. These FMs can be classified into three categories, namely, pathology image FMs, pathology image-text FMs, and pathology image-gene FMs, each of which results in distinct functionalities and application scenarios. This review provides an overview of the latest research advancements in pathological FMs, with a particular emphasis on their applications in oncology. The key challenges and opportunities presented by pathological FMs in precision oncology are also explored.
Humans ; Precision Medicine/methods* ; Medical Oncology/methods* ; Artificial Intelligence ; Neoplasms/pathology* ; Computational Biology/methods*

Humans ; Pre-Eclampsia/diagnosis* ; Pregnancy ; Female ; China ; Evidence-Based Medicine ; Risk Factors

Humans ; Heart Defects, Congenital/therapy* ; Child ; Evidence-Based Medicine ; Cardiac Surgical Procedures/methods* ; Cardiac Catheterization/methods*

Basket trial, as an innovative clinical trial design concept, marks the transformation of medical research from the traditional large-scale and single-disease treatment to the precise and individualized treatment. By gradually incorporating the Bayesian method during development, the trial design becomes more scientific and reasonable and increases its efficiency. The fundamental principle of the Bayesian method is the utilization of prior knowledge in conjunction with new observational data to dynamically update the posterior probability. This flexibility enhances the basket trial's capacity to effectively adapt to variations during the research process. Consequently, it enables researchers to dynamically adjust research strategies based on accumulated data and improve the predictive accuracy regarding treatment responses. In addition, the design concept of the basket trial aligns with the traditional Chinese medicine(TCM) principle of "homotherapy for heteropathy". The principle of "homotherapy for heteropathy" emphasizes that under certain conditions, different diseases may have the same treatment. Similarly, basket trials allow using a uniform trial design across multiple diseases, offering enhanced operational and significant practical value in the realm of TCM, particularly within the context of syndrome-based disease research. By introducing basket trials, the design of TCM clinical studies will be more scientific and yield higher-quality evidence. This study systematically categorized various Bayesian methods and models utilized in basket trials, evaluated their strengths and weaknesses, and identified their appropriate application contexts, so as to offer a practical guide for designing basket trials in the realm of TCM.
Bayes Theorem ; Humans ; Medicine, Chinese Traditional/methods* ; Research Design ; Clinical Trials as Topic/methods* ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: To compare the biomechanical properties of personalized Y-shaped plates with horizontal plates, vertical plates, and traditional Y-shaped plates in the treatment of distal humeral intra-articular fractures through finite element analysis, and to evaluate their potential for clinical application. METHODS: The study selected a 38-year-old male volunteer and obtained a three-dimensional model of the humerus by scanning his upper limbs using a 64-slice spiral CT. Four types of fracture-internal fixation models were constructed using Mimics 19.0, Geomagic Wrap 2017, Creo 6.0, and other software: horizontal plates, vertical plates, traditional Y-shaped plate, and personalized Y-shaped plate. The models were then meshed using Hypermesh 14.0 software, and material properties and boundary conditions were defined in Abaqus 6.14 software. AnyBody 7.3 software was used to simulate elbow flexion and extension movements, calculate muscle strength, joint forces, and load torques, and compare the peak stress and maximum displacement of the four fixation methods at different motion angles (10°, 30°, 50°, 70°, 90°, 110°, 130°, 150°) during elbow flexion and extension. RESULTS: Under dynamic loading during elbow flexion and extension, the personalized Y-shaped plate exhibits significant biomechanical advantages. During elbow flexion, the peak internal fixation stress of the personalized Y-shaped plate was (28.8±0.9) MPa, which was significantly lower than that of the horizontal plates, vertical plates, and traditional Y-shaped plate ( P<0.05). During elbow extension, the peak internal fixation stress of the personalized Y-shaped plate was (18.1±1.6) MPa, which was lower than those of the other three models, with significant differences when compared with horizontal plates and vertical plates ( P<0.05). Regarding the peak humeral stress, the personalized Y-shaped plate model showed mean values of (10.9±0.8) and (13.1±1.4) MPa during elbow flexion and extension, respectively, which were significantly lower than those of the other three models ( P<0.05). Displacement analysis showed that the maximum displacement of the humerus with the personalized Y-shaped plate during elbow flexion was (2.03±0.08) mm, slightly higher than that of the horizontal plates, but significantly lower than that of the vertical plates, showing significant differences ( P<0.05). During elbow extension, the maximum displacement of the humerus with the personalized Y-shaped plate was (1.93±0.13) mm, which was lower than that of the other three models, with significant differences when compared with vertical plates and traditional Y-shaped plates ( P<0.05). Stress contour analysis showed that the stress of the personalized Y-shaped plate was primarily concentrated at the bifurcation of the Y-shaped structure. Displacement contour analysis showed that the personalized Y-shaped plate effectively controlled the displacement of the distal humerus during both flexion and extension, demonstrating excellent stability. CONCLUSION The personalized Y-shaped plate demonstrates excellent biomechanical performance in the treatment of distal humeral intra-articular fractures, with lower stress and displacement, providing more stable fixation effects.
Humans ; Male ; Adult ; Healthy Volunteers ; Finite Element Analysis ; Tomography, Spiral Computed ; Models, Anatomic ; Biomechanical Phenomena ; Humeral Fractures, Distal/surgery* ; Fracture Fixation, Internal/instrumentation* ; Bone Plates ; Computer Simulation ; Precision Medicine/methods* ; Elbow Joint/surgery* ; Elbow/surgery* ; Humerus/surgery* ; Torque ; Stress, Mechanical ; Intra-Articular Fractures/surgery* ; Prosthesis Design/methods* ; Imaging, Three-Dimensional ; Range of Motion, Articular

Hip osteoarthritis (OA) is a significant disease worldwide that causes functional impairment and reduced quality of life. With the aging of the population and the increasing prevalence of obesity, its disease burden is becoming increasingly heavy. In December 2023, the American Academy of Orthopaedic Surgeons (AAOS) released the updated Clinical Practice Guideline for the Management of Osteoarthritis of the Hip (summary). Based on evidence-based medicine, this guideline provides systematic recommendations for the diagnosis and treatment of hip OA. This article will comprehensively interpret the guideline, compare it with relevant domestic expert consensus in China, analyze the consistency and differences in disease management strategies between the two, and provide references for clinical practice.
Humans ; Academies and Institutes ; Arthroplasty, Replacement, Hip ; China ; Evidence-Based Medicine ; Orthopedic Surgeons ; Orthopedics ; Osteoarthritis, Hip/surgery* ; Quality of Life ; United States

Clinical management of Kawasaki disease faces several challenges, including difficulties in early diagnosis, insufficient personalized treatment, delayed access to information, and inefficient multidisciplinary collaboration. This paper explores the application of the DeepSeek AI model in the management of Kawasaki disease: (1) Enhancing early diagnosis accuracy through the integration and analysis of multimodal data (imaging, laboratory, and clinical data); (2) Dynamically adjusting treatment plans to achieve personalized medicine; (3) Integrating the latest global guidelines and research findings in real-time to optimize clinical processes; (4) Providing personalized health education content to enhance parental involvement; (5) Establishing a platform for sharing clinical data to support intelligent decision-making and multidisciplinary collaboration.
Humans ; Mucocutaneous Lymph Node Syndrome/diagnosis* ; Child ; Artificial Intelligence ; Precision Medicine ; East Asian People

OBJECTIVES: To evaluate and integrate evidence on the management of sleep disorders in children with attention deficit hyperactivity disorder (ADHD). METHODS: Literature was retrieved based on the 6S model, and evidence related to sleep disorder management in children with ADHD was extracted from the included references. RESULTS: A total of 17 studies were included, from which 16 pieces of evidence were extracted. Of these, 6 were classified as Level 1 evidence and 10 as Level 5. The evidence covered screening, assessment, non-pharmacological interventions, pharmacological interventions, follow-up, and multidisciplinary collaboration. CONCLUSIONS This study integrated evidence on the management of sleep disorders in children with ADHD using an evidence-based approach, providing an evidence-based foundation for managing sleep disorders in this population.
Humans ; Attention Deficit Disorder with Hyperactivity/complications* ; Sleep Wake Disorders/etiology* ; Child ; Evidence-Based Medicine