Subscribe free

Digital Surgery and Telemedicine ·

Artificial intelligence predicts non-transplantable recurrence in hepatocellular carcinoma

Artificial intelligence models accurately predicted non-transplantable recurrence in hepatocellular carcinoma patients post-hepatic resection. An ensemble AI model showed high accuracy (AUC 0.751-0.858) with incorporation of postoperative factors. Radiologic tumor burden and microvascular invasion were key predictors. Patients with predicted recurrence had lower survival rates, highlighting the models’ prognostic value. The AI models could guide treatment decisions and personalize postoperative care for better outcomes.

Journal Article by Altaf A, Endo Y (…) Pawlik TM et 17 al. in HPB (Oxford)

Copyright © 2024 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

read the whole article in HPB (Oxford)

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 →