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

Samadi, Bahare; Raison, Maxime; Mahaudens, Philippe; Detrembleur, Christine; Achiche, Sofiane; Samadi, Bahare; Raison, Maxime; Mahaudens, Philippe; Detrembleur, Christine; Achiche, Sofiane

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

Bahare Samadi, Maxime Raison , Philippe Mahaudens, Christine Detrembleur, Sofiane Achiche

Article (2023)

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Department:

Department of Mechanical Engineering

PolyPublie URL:

https://publications.polymtl.ca/51874/

Journal Title :

Computer Methods in Biomechanics and Biomedical Engineering ( vol. 26 , no. 11 )

Publisher:

Taylor & Francis

DOI:

10.1080/10255842.2022.2117547

Official URL:

https://doi.org/10.1080/10255842.2022.2117547

OAI:

oai:publications.polymtl.ca:51874

ORCID

Date Deposited:

18 Apr 2023 14:59

Last Modified:

08 Oct 2026 18:27

Cite in APA 7:

Samadi, B., Raison, M., Mahaudens, P., Detrembleur, C., & Achiche, S. (2023). 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. Computer Methods in Biomechanics and Biomedical Engineering, 26(11), 1341-1352. https://doi.org/10.1080/10255842.2022.2117547

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