Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning.

ABSTRACT:

Background

Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective.

Purpose

To develop and independently validate a machine learning mortality risk quantification method for HCC patients using standard-of-care clinical data and liver radiomics on baseline magnetic resonance imaging (MRI).

Methods

This retrospective study included all patients with multiphasic contrast-enhanced MRI at the time of diagnosis treated at our institution. Patients were censored at their last date of follow-up, end-of-observation, or liver transplantation date. The data were randomly sampled into independent cohorts, with 85% for development and 15% for independent validation. An automated liver segm

SUBMITTER: Gross M 

PROVIDER: S-EPMC11399284 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature