BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
11/3/2026 3:34:11 AM | Browse: 1 | Download: 8
 |
Received |
|
2026-06-10 02:49 |
|
Peer-Review Started |
|
2026-06-10 02:50 |
 |
First Decision by Editorial Office Director |
|
|
|
Return for Revision |
|
2026-07-24 01:08 |
|
Revised |
|
2026-08-05 08:14 |
|
Publication Fee Transferred |
|
|
|
Second Decision by Editor |
|
2026-09-11 02:52 |
|
Second Decision by Editor-in-Chief |
|
|
|
Final Decision by Editorial Office Director |
|
2026-09-11 09:20 |
|
Articles in Press |
|
2026-09-11 09:20 |
|
Edit the Manuscript by Language Editor |
|
|
|
Typeset the Manuscript |
|
2026-10-30 09:17 |
|
Publish the Manuscript Online |
|
2026-11-03 03:34 |
| ISSN |
2644-3236 (online) |
| 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/ |
| Copyright |
© The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Minireviews |
| Article Title |
Artificial intelligence-driven risk estimation, early detection, diagnostic characterisation and prognosis in hepatitis b-related hepatocellular carcinoma
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Pranjal Kashiv, Manish Ramesh Balwani, Khushboo Saxena, Priyanka Tolani, Amit Pasari and Vivek B Kute |
| ORCID |
|
| Funding Agency and Grant Number |
|
| Corresponding Author |
Vivek B Kute, Department of Nephrology and Clinical Transplantation, Institute of Kidney Diseases and Research Center, Dr. HL Trivedi Institute of Transplantation Sciences, Room No. 125, First Floor, Civil Hospital Campus, Ahmedabad 380016, Gujarāt, India. drvivekkute@rediffmail.com |
| Key Words |
Hepatitis B; Hepatocellular carcinoma; Artificial intelligence; Deep learning; Risk prediction; Liquid biopsy; Surveillance |
| Core Tip |
Artificial intelligence is applied to four distinct problems in chronic hepatitis B, namely risk estimation, early detection, diagnostic characterisation and prognosis, and this review appraises each separately, reframing hepatocellular carcinoma risk from a static, population-derived score into a dynamic, individualised probability. The discriminative advantage over legacy instruments is reproducible, yet it rests overwhelmingly on retrospective, single-centre, internally validated work in which hepatitis B-specific evidence is a minority. The field’s maturation will be measured not by further increments in the area under the curve but by the rigour of external validation, the candour of calibration, and the equity of deployment. |
| Publish Date |
2026-11-03 03:34 |
| Citation |
Kashiv P, Balwani MR, Saxena K, Tolani P, Pasari A, Kute VB. Artificial intelligence-driven risk estimation, early detection, diagnostic characterisation and prognosis in hepatitis b-related hepatocellular carcinoma. Artif Intell Gastroenterol 2026; 7(3): 124278
|
| URL |
https://www.wjgnet.com/2644-3236/full/v7/i3/124278.htm |
| DOI |
https://doi.org/10.35712/aig.124278 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
