Artificial intelligence in liver cancer surgery: Predicting success before the first incision
Shu-Yen Chan1, Patrick Twohig2
1Department of Internal Medicine, Weiss Memorial Hospital, Chicago, IL 60640, United States.
None:
Advancements in machine learning have revolutionized preoperative risk assessment. In this article, we comment on the article by Huang et al, 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.


