AI-driven prognostic assessment and treatment strategy optimization for hepatocellular carcinoma:technological innovations and advances in clinical translation
10.7659/j.issn.1005-6947.250089
- VernacularTitle:人工智能驱动的肝细胞癌预后评估与治疗策略优化:技术革新与临床转化进展
- Author:
Xiaocheng LI
1
;
Jing PENG
;
Jianping GONG
;
Huai NING
Author Information
1. 湖南医药学院第一附属医院 肝胆外科,湖南 怀化 418000;重庆医科大学附属第二医院 肝胆外科,重庆 400010
- Publication Type:Journal Article
- Keywords:
Carcinoma,Hepatocellular;
Artificial Intelligence;
Deep Learning;
Machine Learning;
Prognosis;
Review
- From:
Chinese Journal of General Surgery
2025;34(7):1498-1504
- CountryChina
- Language:Chinese
-
Abstract:
Hepatocellular carcinoma(HCC)is one of the most prevalent malignancies worldwide,and accurate prognostic assessment and treatment planning are vital for improving patient outcomes.Conventional prognostic models,which rely on limited clinicopathological parameters,often fail to capture the profound heterogeneity of HCC.In recent years,artificial intelligence(AI)-particularly machine learning and deep learning-has driven a paradigm shift in precision oncology by leveraging its powerful capabilities in data mining and pattern recognition.This review provides a comprehensive overview of recent advances in AI for prognostic assessment and treatment optimization in HCC,with an emphasis on key methodologies such as radiomics and multi-modal data integration.It further discusses the clinical potential and challenges of AI in predicting postoperative recurrence,evaluating therapeutic response,and supporting individualized treatment decisions,while also outlining future directions in this rapidly evolving field.The review aims to inform and facilitate the clinical translation of AI technologies into the management of HCC.
