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Development of a machine learning-based radiomics model of perivascular adipose tissue for predicting stroke risk in patients with asymptomatic carotid stenosis: a multicenter study

BackgroundOur work aims to develop and evaluate a combined model that integrates clinical features, conventional computed tomography angiography (CTA) features, and radiomics features of perivascular adipose tissue (PVAT) to identify asymptomatic carotid stenosis (ACS) patients at high risk for shor...

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Principais autores: Jinhong Sun, Cheng Ma, Guihan Lin, Weiyue Chen, Weiming Hu, Zhuohang Shi, Ting Zhao, Jie Zhang, Jianhua Wu, Xiongying Yi, Hua Yang, Suhong Ye, Lei Xu, Yongjun Chen, Weiqian Chen
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2026-01-01
coleção:Frontiers in Radiology
Assuntos:
asymptomatic carotid stenosis
machine learning
perivascular adipose tissue
radiomics
stroke
Acesso em linha:https://www.frontiersin.org/articles/10.3389/fradi.2025.1738298/full
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