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Deep learning for histopathological diagnosis of esophageal squamous cell carcinoma in biopsies: A multicenter analysis | Synapse
March 3, 2026
Deep learning for histopathological diagnosis of esophageal squamous cell carcinoma in biopsies: A multicenter analysis
GX
Guixuan Xu
University of Electronic Science and Technology of China
JZ
Jianmin Zhao
HZ
Haijun Zhang
Shihezi University
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Key Points
Deep learning improves accuracy in diagnosing esophageal squamous cell carcinoma from biopsies, enhancing histopathology.
The model achieved an accuracy of 92% in identifying seminal histopathological features of esophageal carcinoma.
Multicenter analysis across several hospitals provides robust evidence for the effectiveness of the deep learning model.
This study suggests integration of this technology in clinical settings may lead to better diagnostic precision.
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Xu et al. (Sun,) studied this question.
synapsesocial.com/papers/69a76166c6e9836116a2f49d
https://doi.org/https://doi.org/10.1016/j.dld.2026.01.230
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