Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	107414
Country	Tunisia

Received	2025-03-24 07:34
Peer-Review Started	2025-03-24 07:34
To Make the First Decision
Return for Revision	2025-04-01 12:36
Revised	2025-04-14 15:11
Second Decision	2025-05-20 02:45
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-05-20 06:29
Articles in Press	2025-05-20 06:29
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-05-30 03:02
Publish the Manuscript Online	2025-06-13 13:39

ISSN	1948-5204 (online)
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Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Artificial intelligence to predict hepatocellular carcinoma risk in cirrhosis
Manuscript Source	Invited Manuscript
All Author List	Imen Akkari, Hanen Akkari and Raida Harbi
Funding Agency and Grant Number
Corresponding Author	Imen Akkari, Associate Professor, MD, Department of Gastroenterology, University Hospital of Hached, University of Sousse, Faculty of Medicine of Sousse, Rue Mohamed Karoui, Sousse 4000, Tunisia. imenakkaribm@gmail.com
Key Words	Hepatocellular carcinoma; Cirrhosis; Prediction; Artificial intelligence; Prognosis; Machine learning
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.
Publish Date	2025-06-13 13:39
Citation	<p>Akkari I, Akkari H, Harbi R. Artificial intelligence to predict hepatocellular carcinoma risk in cirrhosis. <i>World J Gastrointest Oncol</i> 2025; 17(6): 107414</p>
URL	https://www.wjgnet.com/1948-5204/full/v17/i6/107414.htm
DOI	https://dx.doi.org/10.4251/wjgo.v17.i6.107414

Full Article (PDF)	WJGO-17-107414-with-cover.pdf
Manuscript File	107414_Auto_Edited_065051.docx
Answering Reviewers	107414-answering-reviewers.pdf
Audio Core Tip	107414-audio.m4a
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