학술논문

Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma
Document Type
article
Source
IEEE Access, Vol 12, Pp 37557-37571 (2024)
Subject
Hepatocellular carcinoma (HCC)
viral cancers
artificial intelligence
cancer diagnosis
traditional cancer diagnostic
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Language
English
ISSN
2169-3536
Abstract
Viral and non-viral hepatocellular carcinoma (HCC) is becoming predominant in developing countries. A major issue linked to HCC-related mortality rate is the late diagnosis of cancer development. Although traditional approaches to diagnosing HCC have become gold-standard, there remain several limitations due to which the confirmation of cancer progression takes a longer period. The recent emergence of artificial intelligence tools with the capacity to analyze biomedical datasets is assisting traditional diagnostic approaches for early diagnosis with certainty. Here we present a review of traditional HCC diagnostic approaches versus the use of artificial intelligence (Machine Learning and Deep Learning) for HCC diagnosis. The overview of the cancer-related databases along with the use of AI in histopathology, radiology, biomarker, and electronic health records (EHRs) based HCC diagnosis is given.