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精密骨科的未来:个性化数据驱动的实践

Deiary F Kader¹, Andrew Coppola¹, Aditya Vijay¹

¹South West London Elective Orthopaedic Centre, Epsom, UK.

Bone & joint open

|July 16, 2025

概括

在骨科中,基于证据的医学 (EBM) 通过使用人工智能的个性化数据驱动实践 (PDDP) 得到了增强. 这种混合方法将患者数据整合到量身定制的治疗方法中,改善了精密骨科的结果.

科学领域:

整形外科手术整形外科手术
人工智能的人工智能
个性化医疗是个性化的医疗.

背景情况:

基于证据的医学 (EBM) 和随机对照试验 (RCT) 已经推进了整形外科,但与患者异质性作斗争.
在复杂的情况下,EBM的一刀切性质限制了个性化护理的提供.

研究的目的:

检查EBM和人工智能驱动的个性化数据驱动实践 (PDDP) 在骨科中的互补作用.
突出AI如何增强临床决策和个性化治疗策略.

主要方法:

对用于预测分析和数据集成的AI技术 (机器学习,贝叶斯网络) 的审查.
整合各种数据源:遗传,临床,成像和可穿戴设备数据.
合并EBM原则与人工智能驱动的PDDP的概念框架.

主要成果:

人工智能可实现预测分析,治疗个性化和实时数据集成,用于积极的骨科护理.
结合EBM和AI增强PDDP的混合模型可以改善患者的治疗结果.
挑战包括数据质量,算法透明度,道德和基础设施.

结论:

将人工智能驱动的PDDP与EBM原则合并,为精密骨科创建了一个混合模型.
这种整合支持大数据和人工智能框架内的以患者为中心的护理.
该方法旨在提高结果,同时保持临床医生监督和道德标准.

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