Noninvasive prediction of failure of the conservative treatment in lateral epicondylitis by clinicoradiological features and elbow MRI radiomics based on interpretable machine learning: a multicenter cohort study

Noninvasive prediction of failure of the conservative treatment in lateral epicondylitis by clinicoradiological features and elbow MRI radiomics based on interpretable machine learning: a multicenter cohort study

Abstract Objectives To develop and validate an interpretable machine learning model based on clinicoradiological features and radiomic features based on magnetic resonance imaging (MRI) to predict the failure of conservative treatment in lateral epicondylitis (LE). Methods This retrospective study i...

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Bibliographic Details
Main Authors: Jianing Cui, Ping Wang, Xiaodong Zhang, Ping Zhang, Yuming Yin, Rongjie Bai
Format: Article
Language:English
Published: BMC 2025-05-01
Series:Journal of Orthopaedic Surgery and Research
Subjects:
Lateral epicondylitis
Machine learning
Magnetic resonance imaging
Radiomics
SHapley additive explanation
Online Access:https://doi.org/10.1186/s13018-025-05901-1
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https://doi.org/10.1186/s13018-025-05901-1

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