Interpretable machine learning for detecting symptomatic patients with carotid atherosclerosis on computed tomography angiography: a retrospective diagnostic study

Abstract Background This study aimed to develop a machine learning (ML) model based on radiomics features of carotid plaques and perivascular adipose tissue (PVAT) on computed tomography angiography (CTA) to detect symptomatic carotid atherosclerosis. Methods This retrospective study included patien...

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Autori principali:	Yulu Yang, Jianyong Wei, Xiaoer Wei, Xinyu Song, Zhiwen Yang, Zheng Sun, Chao Zheng, Shundong Hu, Li Zhuo, Yueqi Zhu, Yuehua Li
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2025-12-01
Serie:	BMC Medical Imaging
Soggetti:	Carotid atherosclerosis Perivascular adipose tissue Computed tomography angiography Radiomics Machine learning
Accesso online:	https://doi.org/10.1186/s12880-025-02113-1
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