Application of deep learning upon spinal radiographs to predict progression in adolescent idiopathic scoliosis at first clinic visit

BACKGROUND: Prediction of curve progression risk in adolescent idiopathic scoliosis (AIS) remains elusive. Prior studies have revealed the potential for three-dimensional (3D) morphological parameters to prognosticate progression, but these require specialized biplanar imaging equipment and labor-in...

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Detalles Bibliográficos
Autores principales: Wang, Hongfei, Zhang, Teng, Cheung, Kenneth Man-Chee, Shea, Graham Ka-Hon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8639418/
https://www.ncbi.nlm.nih.gov/pubmed/34901796
http://dx.doi.org/10.1016/j.eclinm.2021.101220

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8639418/
https://www.ncbi.nlm.nih.gov/pubmed/34901796
http://dx.doi.org/10.1016/j.eclinm.2021.101220

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