The Role of Artificial Intelligence in the Detection and Implementation of Biomarkers for Hepatocellular Carcinoma: Outlook and Opportunities

Author:

Mansur Arian1ORCID,Vrionis Andrea2ORCID,Charles Jonathan P.2ORCID,Hancel Kayesha3ORCID,Panagides John C.1ORCID,Moloudi Farzad3ORCID,Iqbal Shams3,Daye Dania3

Affiliation:

1. Harvard Medical School, Boston, MA 02115, USA

2. Morsani College of Medicine, University of South Florida Health, Tampa, FL 33602, USA

3. Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA

Abstract

Liver cancer is a leading cause of cancer-related death worldwide, and its early detection and treatment are crucial for improving morbidity and mortality. Biomarkers have the potential to facilitate the early diagnosis and management of liver cancer, but identifying and implementing effective biomarkers remains a major challenge. In recent years, artificial intelligence has emerged as a promising tool in the cancer sphere, and recent literature suggests that it is very promising in facilitating biomarker use in liver cancer. This review provides an overview of the status of AI-based biomarker research in liver cancer, with a focus on the detection and implementation of biomarkers for risk prediction, diagnosis, staging, prognostication, prediction of treatment response, and recurrence of liver cancers.

Publisher

MDPI AG

Subject

Cancer Research,Oncology

Reference76 articles.

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3. European Association for the Study of the Liver (2018). EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J. Hepatol., 69, 182–236.

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5. Surveillance for Hepatocellular Carcinoma: Current Best Practice and Future Direction;Kanwal;Gastroenterology,2019

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