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 : Better health starts from the ground up
Matthew B Werd, American Academy of Podiatric Sports Medicine (AAPSM), United States
Title : Today’s diagnosis versus tomorrow’s function: What is your focus?
Ron Blehm, EEI Physio LLC, United States
Title : Neuroimaging-based evaluation of scalp acupuncture for neural repair and reorganization in children with cerebral palsy
Zhenhuan Liu, Guangzhou University of Chinese Medicine, China
Title : Managing knowledge-based integration and interoperability in intelligent and ethical transformed health and social care ecosystems
Bernd Blobel, University of Regensburg, Germany