Artificial intelligence in orthopaedic trauma
Chuwei Tian, Yucheng Gao, Rui Chen, Shengbo Qin, Liu Shi, Yunfeng Rui
Abstract
With the exponential growth in data processing capabilities and the progressive intertwining of medicine with industry, artificial intelligence (AI) has gained widespread application in the medical domain. Currently, AI is extensively utilized across various aspects of trauma orthopedics, including fracture identification, diagnosis and stratification, prevention strategies for falls and fractures, emergency management, and perioperative and prognostic risk assessments. This study delves into the research progress and challenges of AI in orthopedic trauma, including the clinical applications of machine learning, deep learning, and natural language processing. By illuminating these dynamic research avenues, this study aimed to catalyze interdisciplinary collaboration and spur innovation at the intersection of AI and orthopedic trauma, ultimately advancing the frontiers of patient care and clinical practice.