Yi PS, Hu CJ, Li CH, Yu F. Clinical value of artificial intelligence in hepatocellular carcinoma: Current status and prospect. Artif Intell Gastroenterol 2021; 2(2): 42-55 [DOI: 10.35712/aig.v2.i2.42]
Corresponding Author of This Article
Fei Yu, MD, Professor, Department of Radiology, Yingshan County People’s Hospital, No. 100 Danan Street, Yingshan County, Nanchong 610041, Sichuan Province, China. 358496734@qq.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/
Clinical value of artificial intelligence in hepatocellular carcinoma: Current status and prospect
Peng-Sheng Yi, Chen-Jun Hu, Chen-Hui Li, Fei Yu
Peng-Sheng Yi, Chen-Jun Hu, Department of Hepato-Biliary-Pancreas II, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Chen-Hui Li, Department of Obstetrics and Gynecology, Nanchong Traditional Chinese Medicine Hospital, Nanchong 637000, Sichuan Province, China
Fei Yu, Department of Radiology, Yingshan County People’s Hospital, Nanchong 610041, Sichuan Province, China
Author contributions: Yu F proposed the idea; Yi PS and Hu CJ wrote the manuscript; Yi PS and Hu CJ contributed equally to this work; Li CH performed the electronic searching and abstracted the data.
Supported byProject of Science and Technology Department of Sichuan Province, No. 2018JY050; and Nanchong Science and Technology Bureau Project, No. 18SXHZ0336.
Conflict-of-interest statement: The authors declare that they have no competing interests.
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: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fei Yu, MD, Professor, Department of Radiology, Yingshan County People’s Hospital, No. 100 Danan Street, Yingshan County, Nanchong 610041, Sichuan Province, China. 358496734@qq.com
Received: January 6, 2021 Peer-review started: January 6, 2021 First decision: February 14, 2021 Revised: February 25, 2021 Accepted: March 15, 2021 Article in press: March 15, 2021 Published online: April 28, 2021 Processing time: 108 Days and 17.4 Hours
Abstract
Hepatocellular carcinoma (HCC) is the most commonly diagnosed type of liver cancer and the fourth leading cause of cancer-related mortality worldwide. The early identification of HCC and effective treatments for it have been challenging. Due to the sufficient compensatory ability of early patients and its nonspecific symptoms, HCC is more likely to escape diagnosis in the incipient stage, during which patients can achieve a more satisfying overall survival if they undergo resection or liver transplantation. Patients at advanced stages can profit from radical therapies in a limited way. In order to improve the unfavorable prognosis of HCC, diagnostic ability and treatment efficiency must be improved. The past decade has seen rapid advancements in artificial intelligence, underlying its unique usefulness in almost every field, including that of medicine. Herein, we sought and reviewed studies that put emphasis on artificial intelligence and HCC.
Core Tip: We performed electronic searching in PubMed, Web of Science and EMBASE. Artificial intelligence (AI) or in-depth learning and hepatocellular carcinoma were used as mesh terms. We found that AI showed favorable results in early diagnosis and treatment response prediction and prognosis estimation in patients with hepatocellular carcinoma. The past decade has seen rapid advancements in AI, underlying its unique usefulness in almost every field, including that of medicine. Herein, we sought and reviewed studies, and we expect that AI will be an important complement to traditional diagnosis, treatment and prognosis estimation of hepatocellular carcinoma.
