Prediction of cervical cancer lymph node metastasis based on multisequence magnetic resonance imaging radiomics and deep learning features: a dual-center study

Prediction of cervical cancer lymph node metastasis based on multisequence magnetic resonance imaging radiomics and deep learning features: a dual-center study

Abstract Cervical cancer is a leading cause of death from malignant tumors in women, and accurate evaluation of occult lymph node metastasis (OLNM) is crucial for optimal treatment. This study aimed to develop several predictive models—including Clinical model, Radiomics models (RD), Deep Learning m...

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Bibliographic Details
Main Authors: Shigang Luo, Yan Guo, Yongqing Ye, Qinglin Mu, Wenguang Huang, Guangcai Tang
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Radiomics
Deep learning
Occult lymph node metastasis
Cervical cancer
Online Access:https://doi.org/10.1038/s41598-025-13781-y
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https://doi.org/10.1038/s41598-025-13781-y

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