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Radiomic features and carotid stenosis in periodontitis a two stage bootstrap and multimodal machine learning study

Abstract This study aims to develop and validate a deep learning model based on Cone Beam Computed Tomography (CBCT) radiomic features to achieve early detection of potential carotid atherosclerosis in periodontitis patients. The study utilised data from 279 observations, each with 206 features, to...

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Main Authors: Mengqiang Zhang, Jing Cai, Qian Cao, Zhipeng Chen, Subinuer Maimaitiaili, Shaoxun Yuan, Tao Yang, Zhen Li, Zhen Zhang, Yun Yang, Tong Qiao
Format: Artigo
Language:Inglês
Published: Nature Portfolio 2026-02-01
Series:Scientific Reports
Subjects:
Radiomics
Carotid atherosclerosis
Periodontitis
Machine learning
Early diagnosis
Online Access:https://doi.org/10.1038/s41598-026-38463-1
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