Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.
Journal:
HPB : the official journal of the International Hepato Pancreato Biliary Association
Published Date:
Mar 4, 2025
Abstract
BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellular carcinoma (HCC) remains challenging. Nonetheless, effective tools to assess MILS complexity are still lacking. Machine learning (ML) models could improve the accuracy of such tools.
Authors
Keywords
Aged
Carcinoma, Hepatocellular
Databases, Factual
Decision Support Techniques
Female
Hepatectomy
Humans
Liver Neoplasms
Machine Learning
Male
Middle Aged
Minimally Invasive Surgical Procedures
Predictive Value of Tests
Retrospective Studies
Risk Assessment
Risk Factors
Treatment Outcome
Tumor Burden