Prediction of esophageal fistula in radiotherapy/chemoradiotherapy for patients with advanced esophageal cancer by a clinical-deep learning radiomics model

Prediction of esophageal fistula in radiotherapy/chemoradiotherapy for patients with advanced esophageal cancer by a clinical-deep learning radiomics model

Abstract Background Esophageal fistula (EF), a rare and potentially fatal complication, can be better managed with predictive models for personalized treatment plans in esophageal cancers. We aim to develop a clinical-deep learning radiomics model for effectively predicting the occurrence of EF. Met...

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Bibliographic Details
Main Authors: Yuxin Zhang, Xu Cheng, Xianli Luo, Ruixia Sun, Xiang Huang, Lingling Liu, Min Zhu, Xueling Li
Format: Article
Language:English
Published: BMC 2024-11-01
Series:BMC Medical Imaging
Subjects:
Esophageal fistula
Deep learning
Predictive model
Radiomics
Online Access:https://doi.org/10.1186/s12880-024-01473-4
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https://doi.org/10.1186/s12880-024-01473-4

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