Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study

Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study

Abstract Objectives To develop and validate a magnetic resonance imaging-based (MRI) deep multiple instance learning (D-MIL) model and combine it with clinical parameters for preoperative prediction of lymph node metastasis (LNM) in operable cervical cancer. Methods A total of 392 patients with cerv...

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Bibliographic Details
Main Authors: Fengying Qin, Xinyan Sun, Mingke Tian, Shan Jin, Jian Yu, Jing Song, Feng Wen, Hongming Xu, Tao Yu, Yue Dong
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Insights into Imaging
Subjects:
Lymph node metastasis
Cervical cancer
Deep learning
Magnetic resonance imaging
Online Access:https://doi.org/10.1186/s13244-024-01618-7

Internet

https://doi.org/10.1186/s13244-024-01618-7

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