Progression risk of adolescent idiopathic scoliosis based on SHAP-Explained machine learning models: a multicenter retrospective study

Progression risk of adolescent idiopathic scoliosis based on SHAP-Explained machine learning models: a multicenter retrospective study

Abstract Objective To develop an interpretable machine learning model, explained using SHAP, based on imaging features of adolescent idiopathic scoliosis extracted by convolutional neural networks (CNNs), in order to predict the risk of curve progression and identify the most accurate predictive mod...

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Bibliographic Details
Main Authors: Xinyi Fang, Ting Weng, Zhehao Zhang, Wanfeng Gong, Yu Zhang, Mei Wang, Jianhua Wang, Zhongxiang Ding, Can Lai
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Musculoskeletal Disorders
Subjects:
Idiopathic scoliosis
Machine learning
Model prediction
SHAP
Online Access:https://doi.org/10.1186/s12891-025-08841-3
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