Machine Learning-based Radiomic Model for Early Diagnosis of Male Urethral Injury in Pelvic Fracture Patients

Background and objective: Pelvic fracture urethral injury (PFUI) is serious and requires prompt diagnosis. Traditional diagnostic methods, which rely on clinical evaluation and invasive imaging, are subjective and can cause delays. This study aims to utilize machine learning and radiomics to improve...

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Autori principali:	Yongdong Pan, Yubo Gu, Ruihang Zhang, Tianzheng Hao, Jianwen Huang, Weidong Zhu, Guoping Song, Lujie Song
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-03-01
Serie:	European Urology Open Science
Soggetti:	Pelvic fracture urethral injury Radiomics Machine learning Nomogram Computed tomography Feature selection
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2666168325024942
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