Stacked CT radiomics, deep learning and clinical feature models for differentiating benign and malignant solitary pulmonary nodules

Abstract Solitary pulmonary nodules (SPNs) are common incidental findings on high-resolution CT, and differentiating benign from malignant lesions still depends mainly on invasive biopsy, highlighting the need for accurate non-invasive tools. In this retrospective multicenter study we analyzed 201 S...

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Auteurs principaux:	Jie Zong, Biyun Jiang, Haiyan Li, Zhiling Li
Format:	Artigo
Langue:	Inglês
Publié:	Nature Portfolio 2026-04-01
Collection:	Scientific Reports
Sujets:	Solitary pulmonary nodule Probability stacking Radiomics Deep learning Serological biomarkers
Accès en ligne:	https://doi.org/10.1038/s41598-026-49720-8
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