Subscribe free

Digital Surgery and Telemedicine ·

AI Model Effectively Quantifies Residual Pancreatic Cancer Post-Treatment

Development and validation of the ISGPP model marks a significant advancement in automating residual pancreatic cancer (RPC) quantification. The model demonstrated robust performance across diverse scanners, achieving mean F1 scores of 0.81-0.71 upon validation. A comprehensive dataset of 528 unique H&E slides from 528 patients facilitated training the model, which is now publicly available. This innovation supports objective evaluation of neoadjuvant treatment responses in pancreatic cancer, filling a critical gap in the assessment process.

• Why it matters: Automated RPC quantification enhances treatment response assessment in oncology.

Journal Article by Janssen BV, Oteman B (…) de Boer OJ et 25 al. in Am J Surg Pathol

Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.

read the whole article in Am J Surg Pathol

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 →