Artificial intelligence in liver cancer surgery: Predicting success before the first incision.
Journal:
World journal of gastroenterology
PMID:
40308801
Abstract
Advancements in machine learning have revolutionized preoperative risk assessment. In this article, we comment on the article by Huang , which presents a recent multicenter cohort study demonstrated that machine learning algorithms effectively stratify recurrence-free survival, providing a robust predictive framework for maximizing surgical outcomes in intrahepatic cholangiocarcinoma. By leveraging interpretable models, the research enhances clinical decision-making, allowing for more precise patient selection and personalized surgical strategies. These findings highlight the growing role of artificial intelligence in optimizing surgical outcomes and improving prognostic accuracy in hepatobiliary oncology.