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

To assess the severity and progression of adolescents with idiopathic scoliosis (AIS), radiography with X-rays is usually used. The methods based on statistical observations have been developed from 3D reconstruction of the trunk or topography. Machine learning has shown great potential to classify...

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Bibliographic Details
Published in:	Computer methods in biomechanics and biomedical engineering Vol. 26; no. 11; pp. 1341 - 1352
Main Authors:	Samadi, Bahare, Raison, Maxime, Mahaudens, Philippe, Detrembleur, Christine, Achiche, Sofiane
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 18.08.2023 Taylor & Francis Ltd
Subjects:	Adolescents Algorithms Classification Gait gait analysis idiopathic scoliosis Image reconstruction intervertebral efforts Learning algorithms Machine learning Machine-learning classification algorithms Multilayer perceptrons non-invasive spinal deformity evaluation Radiation Radiography Scoliosis Spine Spine (lumbar) Statistical methods Support vector machines
ISSN:	1025-5842, 1476-8259, 1476-8259
Online Access:	Get full text
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