Machine learning-assisted classification of hip conditions in pediatric cerebral palsy patients using migration percentage measurements

Machine learning-assisted classification of hip conditions in pediatric cerebral palsy patients using migration percentage measurements

Hip displacement is a significant concern in children with cerebral palsy (CP), necessitating accurate and timely assessment to prevent long-term complications. This study developed a support vector machine (SVM) model to classify hip conditions using migration percentage (MP) measurements obtained...

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Bibliographic Details
Main Authors: Sema Ertan Birsel, Ekrem Demirci, Ali Seker, Kadriye Yasemin Usta Ayanoğlu, Emir Oncu, Fatih Ciftci
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Bone Reports
Subjects:
Artificial intelligence
Bone diseases
Case study
Cerebral palsy
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352187225000294
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http://www.sciencedirect.com/science/article/pii/S2352187225000294

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