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Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma
- Asif, Arun;
- Ahmed, Faheem;
- Zeeshan;
- Khan, Javed Ali;
- Allogmani, Eman;
- ... Anwar, Muhammad Shahid;
- 외 2명
WEB OF SCIENCE
4SCOPUS
6초록
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.
키워드
- 제목
- Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma
- 저자
- Asif, Arun; Ahmed, Faheem; Zeeshan; Khan, Javed Ali; Allogmani, Eman; El Rashidy, Nora; Manzoor, Sobia; Anwar, Muhammad Shahid
- 발행일
- 2024-02
- 유형
- Article
- 저널명
- IEEE Access
- 권
- 12
- 페이지
- 37557 ~ 37571
- 언어
- ENG
- 출판사
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- 발행국가
- 미국
- 분량
- 15 페이지
- ISSN
- P 2169-3536