Deik Andres
Department of Neurology, Division of Movement Disorders, University of Pennsylvania, Philadelphia, Pennsylvania.
Semin Neurol. 2025 May 26. doi: 10.1055/a-2596-5950.
Artificial intelligence (AI) has emerged as a transformative force in the management of movement disorders. This review explores the various applications of AI across the spectrum of care, from diagnosis to clinical workflows, treatment, and monitoring. Recent advancements include deep phenotyping tools like the Next Move in Movement Disorders (NEMO) project for hyperkinetic disorders, diagnostic platforms such as DystoniaNet, and biomarker identification systems for early Parkinson's disease detection. AI may revolutionize treatment selection through technologies like DystoniaBoTXNet and adaptive deep brain stimulation systems. For symptom monitoring, innovations like the Emerald device and smartphone-based assessment tools enable continuous, objective evaluation. AI may also enhance patient care through improved telemedicine capabilities and ambient listening. Despite these promising developments, recent critiques highlight methodological concerns in AI research, emphasizing the need for rigorous validation and transparency. The future of AI in movement disorders requires balancing technological innovation with clinical expertise to improve patient outcomes.
人工智能(AI)已成为运动障碍管理中的一股变革力量。本综述探讨了AI在整个护理领域的各种应用,从诊断到临床工作流程、治疗和监测。最近的进展包括用于运动亢进性疾病的深度表型分析工具,如运动障碍中的下一步行动(NEMO)项目、肌张力障碍网络等诊断平台,以及用于早期帕金森病检测的生物标志物识别系统。AI可能通过肌张力障碍肉毒毒素网络和自适应深部脑刺激系统等技术彻底改变治疗选择。对于症状监测,像翡翠设备和基于智能手机的评估工具等创新能够实现持续、客观的评估。AI还可能通过改进远程医疗能力和环境监听来提升患者护理水平。尽管有这些令人鼓舞的发展,但最近的批评强调了AI研究中的方法学问题,强调需要进行严格的验证和保持透明度。运动障碍领域中AI的未来需要在技术创新与临床专业知识之间取得平衡,以改善患者的治疗效果。