3rd Edition of Global Conference on
Physical Medicine and Rehabilitation
September 15-17, 2025 | London, UK
AI, Machine Learning, and Big Data
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.
Mel Glenn
Harvard Medical School, United States
Chadwick C Prodromos
Rush University, United States
Marcia J Scherer
Institute for Matching Person and Technology, United States
Roger H Coletti
Interventional Health, United States
Archana Vatwani
Old Dominion University, United States
Elizabeta Popova Ramova
MIT University, Republic of North Macedonia
Ron Blehm
EEI Physio LLC, United StatesSubmit your abstract Today
Title : Exploring the use of technology in inpatient rehabilitation hospitals
Elissa Charbonneau, Encompass Health, United States
Title : Treatment of chronic muscle spasm and pain with the CMECD® procedure
Roger H Coletti, Interventional Health, United States
Title : The technology we have, the technology we use, the technology we want
Marcia J Scherer, Institute for Matching Person and Technology, United States
Title : Best practice guidelines for the use of pharmacological neuromodulation in disorders of diminished motivation: A comprehensive approach
Vaidya Balasubramaniam, The Wollongong Hospital (ISLHD), Australia
Title : Integrating holistic early rehabilitation in acute care: Evidence-Based strategies for enhancing patient outcomes and optimizing costs
Archana Vatwani, Old Dominion University, United States
Title : Indications for Shockwave in Teenage Athletes
Jay Spector, American Academy of Podiatric Sports Medicine (AAPSM), United States