A preliminary study in classification of the severity of spine deformation in adolescents with lumbar/thoracolumbar idiopathic scoliosis using machine learning algorithms based on lumbosacral joint efforts during gait-Reference-Cited by-同舟云学术

A preliminary study in classification of the severity of spine deformation in adolescents with lumbar/thoracolumbar idiopathic scoliosis using machine learning algorithms based on lumbosacral joint efforts during gait

Published:2022-09-10 Issue: Volume: Page:1-12
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Samadi Bahare¹²,Raison Maxime¹²,Mahaudens Philippe³⁴,Detrembleur Christine⁴^ORCID,Achiche Sofiane¹

Affiliation:

1. Department of Mechanical Engineering, Polytechnique Montréal, Montreal, QC, Canada

2. Technopole in Pediatric Rehabilitation Engineering, Sainte-Justine UHC, Montreal, Canada

3. Service d’orthopédie et de traumatologie de l’appareil locomoteur, Cliniques universitaires Saint-Luc, Brussels, Belgium

4. Secteur des Sciences de la Santé, Institut de Recherche Expérimentale et Clinique, Neuro Musculo Skeletal Lab (NMSK), Université catholique de Louvain, Brussels, Belgium

Funder

Fonds de Recherche du Québec – Nature et Technologies

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2022.2117547

Reference60 articles.

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1. Applications of artificial intelligence for adolescent idiopathic scoliosis: mapping the evidence;Spine Deformity;2024-08-17

2. Explainable Deep-Learning-Based Gait Analysis of Hip–Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression;Sensors;2024-07-12