Zhang W, Song LN, You YF, Qi FN, Cui XH, Yi MX, Zhu G, Chang RA, Zhang HJ. Application of artificial intelligence in the prediction of immunotherapy efficacy in hepatocellular carcinoma: Current status and prospects. Artif Intell Gastroenterol 2024; 5(1): 90096 [DOI: 10.35712/aig.v5.i1.90096]
Corresponding Author of This Article
Hai-Jian Zhang, MD, PhD, Professor, Research Scientist, Research Center of Clinical Medicine, The Affiliated Hospital of Nantong University, No. 20 West Temple Road, Nantong 226001, Jiangsu Province, China. hjzhang@ntu.edu.cn
Research Domain of This Article
Computer Science, Artificial Intelligence
Article-Type of This Article
Editorial
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/
Wei Zhang, Li-Ning Song, Yun-Fei You, Feng-Nan Qi, Ming-Xun Yi, Ren-An Chang, Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
Xiao-Hong Cui, Department of General Surgery, Shanghai Electric Power Hospital, Shanghai 200050, China
Guang Zhu, Hai-Jian Zhang, Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China
Hai-Jian Zhang, Research Center of Clinical Medicine, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
Author contributions: Zhang W and Zhang HJ have access to all the data in this study and take responsibility for the integrity and accuracy of the data analyses. Zhang HJ, Zhu G, and Chang RA study concept and design; Zhang W drafted the manuscript; Song LN revised the manuscript; You YF, Qi FN, Cui XH, and Yi MX supervised the study and provided modification suggestions; All authors have read and approved the final manuscript; Zhang W and Song LN contributed equally to this work.
Supported bythe National Natural Science Foundation of China, No. 81401988; China Postdoctoral Science Foundation, No. 2019M661907; Jiangsu Postdoctoral Science Foundation, No. 2019K159, and No. 2019Z153; General Project of Jiangsu Provincial Health Committee, No. H2023136; General Project of Nantong Municipal Health Committee, No. MS2023013; Jiangsu Provincial Research Hospital, No. YJXYY202204-YSB28; and College Student Innovation Program, No. 202210304128Y, and No. 2023103041055.
Conflict-of-interest statement: All authors certify that they have no conflicts of interest related to this work.
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: Hai-Jian Zhang, MD, PhD, Professor, Research Scientist, Research Center of Clinical Medicine, The Affiliated Hospital of Nantong University, No. 20 West Temple Road, Nantong 226001, Jiangsu Province, China. hjzhang@ntu.edu.cn
Received: November 23, 2023 Peer-review started: November 23, 2023 First decision: January 12, 2024 Revised: January 28, 2024 Accepted: March 12, 2024 Article in press: March 12, 2024 Published online: April 30, 2024 Processing time: 158 Days and 5.8 Hours
Abstract
Artificial Intelligence (AI) has increased as a potent tool in medicine, with promising oncology applications. The emergence of immunotherapy has transformed the treatment terrain for hepatocellular carcinoma (HCC), offering new hope to patients with this challenging malignancy. This article examines the role and future of AI in forecasting the effectiveness of immunotherapy in HCC. We highlight the potential of AI to revolutionize the prediction of therapy response, thus improving patient selection and clinical outcomes. The article further outlines the challenges and future research directions in this emerging field.
Core Tip: Recently, there has been a lot of progress in predicting the effect of immunotherapy for hepatocellular carcinoma using artificial intelligence, but it also faces serious challenges. Therefore, in this article we summarize and discuss these issues.