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.
Original language | English |
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Pages (from-to) | 37557-37571 |
Number of pages | 15 |
Journal | IEEE Access |
Volume | 12 |
Early online date | 23 Feb 2024 |
DOIs | |
Publication status | E-pub ahead of print - 23 Feb 2024 |
Keywords
- artificial intelligence
- cancer diagnosis
- Hepatocellular carcinoma (HCC)
- traditional cancer diagnostic
- viral cancers