The application of AI, machine learning, and big data in PM&R is revolutionizing rehabilitation by enabling predictive analytics, personalized treatment plans, and automated assessments. AI-driven gait analysis and motion capture systems provide real-time feedback, optimizing movement correction and therapy outcomes. Machine learning models are refining diagnosis accuracy by identifying patterns in complex rehabilitation data, while big data integration helps clinicians track patient progress and predict recovery trajectories. Virtual assistants and chatbots are also enhancing patient engagement by providing continuous support and therapy reminders. As artificial intelligence continues to advance, rehabilitation practices are becoming more adaptive, data-driven, and responsive to individual patient needs.
Title : Disorders of diminished motivation: Diagnosis, assessment treatment, and emerging treatment options: A rehabilitation perspective
Vaidya Balasubramaniam, Illawarra and Shoalhaven Local Health District Hospitals, Australia
Title : Best practice guidelines for the use of pharmacological neuromodulation in disorders of diminished motivation: A comprehensive approach
Vaidya Balasubramaniam, Illawarra and Shoalhaven Local Health District Hospitals, Australia
Title : Chronic Fatigue Syndrome(CFS) and Myalgia Encephalomyelitis (ME): A literature review on management principles and emerging therapies
Vaidya Balasubramaniam, Illawarra and Shoalhaven Local Health District Hospitals, Australia
Title : Orthopaedic manual therapy for TemporoMandibular Disorders (TMD): Integrating osteopathic techniques with physiotherapy
Srdjan Andjelkov, Manual Physical Therapy, Serbia
Title : The Role of a mobile cancer team in supporting interdisciplinary care for oncology patients in the acute inpatient rehab level of care
Blair Gorenberg, Shirley Ryan Abilitylab, United States