Subscribe free

Digital Surgery and Telemedicine ·

Deep learning model predicts early recurrence in gastric cancer

A new deep learning model utilizing multiphase CT images effectively predicts early recurrence in patients with locally advanced gastric cancer (LAGC). The model, integrated with clinical factors, demonstrated superior performance (AUC: 0.891) compared to previous models. Significant associations were found between higher prediction scores and tumor proliferation pathways, such as WNT and MYC signaling, as well as immune cell infiltration. This tool aids in optimizing treatment strategies and monitoring patient outcomes following surgery.

Multicenter Study by Guo X, Chen M (…) Ji J et 10 al. in Int J Surg

Copyright © 2025 The Author(s). Published by Wolters Kluwer Health, Inc.

read the whole article in Int J Surg

open it in PubMed

Summaries are written to help you decide what to read. They do not replace the full paper.

Free · 5 minutes a day

Get every new paper in Digital Surgery and Telemedicine.

Plus the Daily Selection: the five most relevant papers of the day, each cut to its key points.

Specialty newsletters: every new paper in your field, as a list of titles linked to the source. Daily Selection: the five that matter, cut to their key points.

FreeNo spamOne-click unsubscribe

More in Digital Surgery and Telemedicine

The latest stitches

Digital Surgery and Telemedicine20 Oct 2026

AI Segments Abdominal Wall Layers During Trocar Entry

In a 10-procedure pilot, deep learning identified abdominal wall layers in optical trocar-entry video with promising accuracy—but this is not yet evidence of safer access.

All papers in Digital Surgery and Telemedicine →