APA (7th ed.) Citation

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

Chicago Style (17th ed.) Citation

Samadi, Bahare, Maxime Raison, Philippe Mahaudens, Christine Detrembleur, and Sofiane Achiche. "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, no. 11 (2023): 1341-1352. https://doi.org/10.1080/10255842.2022.2117547.

MLA (9th ed.) Citation

Samadi, Bahare, et al. "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, vol. 26, no. 11, 2023, pp. 1341-1352, https://doi.org/10.1080/10255842.2022.2117547.