Akkari I, Akkari H, Harbi R. Artificial intelligence to predict hepatocellular carcinoma risk in cirrhosis. World J Gastrointest Oncol 2025; 17(6): 107414 [DOI: 10.4251/wjgo.v17.i6.107414]
Corresponding Author of This Article
Imen Akkari, MD, Associate Professor, Department of Gastroenterology, University Hospital of Hached, University of Sousse, Faculty of Medicine of Sousse, Rue Mohamed Karoui, Sousse 4000, Tunisia. imenakkaribm@gmail.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastrointest Oncol. Jun 15, 2025; 17(6): 107414 Published online Jun 15, 2025. doi: 10.4251/wjgo.v17.i6.107414
Artificial intelligence to predict hepatocellular carcinoma risk in cirrhosis
Imen Akkari, Hanen Akkari, Raida Harbi
Imen Akkari, Department of Gastroenterology, University Hospital of Hached, University of Sousse, Faculty of Medicine of Sousse, Sousse 4000, Tunisia
Hanen Akkari, LATIS-Laboratory of Advanced Technology and Intelligent Systems, University of Sousse, National School of Engineering of Sousse, Sousse 4023, Tunisia
Raida Harbi, Department of Gastroenterology, University Hospital of Sahloul, University of Sousse, Faculty of Medicine of Sousse, Sousse 4054, Tunisia
Author contributions: Akkari I and Akkari H conceptualized and designed the report; Akkari I, Akkari H, and Harbi R wrote the manuscript; Harbi R performed the literature review; All authors read and approved the final manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Imen Akkari, MD, Associate Professor, Department of Gastroenterology, University Hospital of Hached, University of Sousse, Faculty of Medicine of Sousse, Rue Mohamed Karoui, Sousse 4000, Tunisia. imenakkaribm@gmail.com
Received: March 24, 2025 Revised: April 14, 2025 Accepted: May 20, 2025 Published online: June 15, 2025 Processing time: 83 Days and 2.2 Hours
Abstract
Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths worldwide. The primary risk factor for HCC is cirrhosis. Identifying individuals who are at high risk of developing HCC will have numerous benefits for patient outcomes, patient quality of life, and the global healthcare system. Artificial intelligence (AI) has the capability to develop systems that emulate human intelligence. Recent studies have highlighted the potential of AI in the management of HCC, and the application of AI appears promising for identifying high-risk groups among patients with cirrhosis who require closer monitoring. Ultimately, the aim of AI in the field of HCC clinical care is to enable earlier diagnosis and consequently improve prognosis.
Core Tip: Hepatocellular carcinoma (HCC) is a global health problem and cirrhosis is the principal risk factor for its development. Early diagnosis of HCC is associated with a better prognosis because curative treatment is feasible. The recommended screening strategy for patients with cirrhosis is ultrasound evaluation twice per year. However, the risk estimation of HCC is not the same in patients with cirrhosis, and as such risk stratification scores have been a focus of study in this population. The application of artificial intelligence has shown promise in screened patients with cirrhosis who are at the highest risk of developing HCC.
