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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.
Andres Deik (Tue,) studied this question.