CT-based machine learning model integrating intra- and peri-tumoral radiomics features for predicting occult lymph node metastasis in peripheral lung cancer

CT-based machine learning model integrating intra- and peri-tumoral radiomics features for predicting occult lymph node metastasis in peripheral lung cancer

Abstract Background Accurate preoperative assessment of occult lymph node metastasis (OLNM) plays a crucial role in informing therapeutic decision-making for lung cancer patients. Computed tomography (CT) is the most widely used imaging modality for preoperative work-up. The aim of this study was to...

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Bibliographic Details
Main Authors: Xiaoyan Lu, Fan Liu, Jiahui E, Xiaoting Cai, Jingyi Yang, Xueqi Wang, Yuwei Zhang, Bingsheng Sun, Ying Liu
Format: Article
Language:English
Published: BMC 2025-08-01
Series:Cancer Imaging
Subjects:
Lung cancer
Radiomics
Occult lymph node metastasis
Tumor
Peritumoral
Online Access:https://doi.org/10.1186/s40644-025-00928-3
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https://doi.org/10.1186/s40644-025-00928-3

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