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 and 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
Date Deposited:	18 Apr 2023 14:59
Last Modified:	25 Sep 2024 16:42

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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