Application of machine learning-based radiomics in osteoporotic vertebral fractures
ZHENG Zhouyang
TANG Guangyu
Abstract：Osteoporotic vertebral fracture(OVF)is characterized by high incidence and high disability rate.Machine learning(ML)-based radiomics studies have increasingly focused on the full-process management of this disease.This paper describes the current research status of ML in three key aspects of OVF:prediction and risk assessment,diagnosis and classification/grading,and prognosis and treatment response evaluation.It highlights recent research progress of ML in solving core clinical problems such as OVF prediction,differentiation of acute and chronic OVF,and OVF refracture,aiming to provide a reference for more accurate and effective integration of ML technologies into the clinical diagnosis and treatment pathway of OVF.
Keywords：Osteoporotic vertebral fractureArtificial intelligenceMachine learningRadiomicsMagnetic resonance imagingTomographyX-ray computed
Publication Date：2026-03-15
Online Publishing Date：2026-04-01(First online date of this platform, not the publication date of the document)
Pages：5( 220-224 )