Development of an Interpretable Deep Learning Model for Pathological Tumor Response Assessment After Neoadjuvant Therapy

Development of an Interpretable Deep Learning Model for Pathological Tumor Response Assessment After Neoadjuvant Therapy

Abstract Background Neoadjuvant therapy followed by surgery has become the standard of care for locally advanced esophageal squamous cell carcinoma (ESCC) and accurate pathological response assessment is critical to assess the therapeutic efficacy. However, it can be laborious and inconsistency betw...

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Bibliographic Details
Main Authors: Yichen Wang, Wenhua Zhang, Lijun Chen, Jun Xie, Xuebin Zheng, Yan Jin, Qiang Zheng, Qianqian Xue, Bin Li, Chuan He, Haiquan Chen, Yuan Li
Format: Article
Language:English
Published: BMC 2024-04-01
Series:Biological Procedures Online
Subjects:
Pathological Tumor Response
Immunochemotherapy
Esophageal Squamous Carcinoma
Knowledge Distillation
Semi-supervised Learning
Online Access:https://doi.org/10.1186/s12575-024-00234-5

Internet

https://doi.org/10.1186/s12575-024-00234-5

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