Machine learning methods in physical therapy: A scoping review of applications in clinical context.

Journal: Musculoskeletal science & practice

Published Date: Sep 13, 2024

BACKGROUND: Machine learning (ML) efficiently processes large datasets, showing promise in enhancing clinical practice within physical therapy.

Felipe J J Reis

Department of Physical Therapy, Federal Institute of Rio de Janeiro, Rio de Janeiro, Brazil; Pain in Motion Research Group, Department of Physical Therapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium; School of Physical and Occupational Therapy, McGill University, Montreal, Canada. Electronic address: felipe.reis@ifrj.edu.br.
Matheus Bartholazzi Lugão de Carvalho

Physical Therapy Department, Instituto Federal do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ, Brazil.
Gabriela de Assis Neves

Physical Therapy Department, Instituto Federal do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ, Brazil.
Leandro Calazans Nogueira

Physical Therapy Department, Instituto Federal do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ, Brazil; Postgraduate Program in Rehabilitation Sciences, Centro Universitário Augusto Motta (UNISUAM), Rio de Janeiro, RJ, Brazil.
Ney Meziat-Filho

Postgraduate Program in Rehabilitation Sciences, Centro Universitário Augusto Motta (UNISUAM), Rio de Janeiro, RJ, Brazil; School of Rehabilitation Sciences, Faculty of Health Sciences, Institute of Applied Health Sciences, McMaster University, Hamilton, ON, Canada.

Female Humans Machine Learning Male Physical Therapy Modalities

View on PubMed Access via DOI PubMed (39278141)