Desai Vishal
Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania.
Semin Musculoskelet Radiol. 2024 Apr;28(2):203-212. doi: 10.1055/s-0043-1778019. Epub 2024 Mar 14.
Artificial intelligence (AI) has shown tremendous growth over the last decade, with the more recent development of clinical applications in health care. The ability of AI to synthesize large amounts of complex data automatically allows health care providers to access previously unavailable metrics and thus enhance and personalize patient care. These innovations include AI-assisted diagnostic tools, prediction models for each treatment pathway, and various tools for workflow optimization. The extension of AI into sports medicine is still early, but numerous AI-driven algorithms, devices, and research initiatives have delved into predicting and preventing athlete injury, aiding in injury assessment, optimizing recovery plans, monitoring rehabilitation progress, and predicting return to play.
在过去十年中,人工智能(AI)取得了巨大发展,近期在医疗保健领域的临床应用也有所进展。人工智能自动合成大量复杂数据的能力,使医疗保健提供者能够获取以前无法获得的指标,从而加强并个性化患者护理。这些创新包括人工智能辅助诊断工具、针对每种治疗途径的预测模型以及各种用于优化工作流程的工具。人工智能在运动医学领域的应用尚处于早期阶段,但众多由人工智能驱动的算法、设备和研究项目已深入研究预测和预防运动员损伤、辅助损伤评估、优化恢复计划、监测康复进展以及预测重返赛场的情况。