Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Asif, Arun | - |
dc.contributor.author | Ahmed, Faheem | - |
dc.contributor.author | Zeeshan | - |
dc.contributor.author | Khan, Javed Ali | - |
dc.contributor.author | Allogmani, Eman | - |
dc.contributor.author | El Rashidy, Nora | - |
dc.contributor.author | Manzoor, Sobia | - |
dc.contributor.author | Anwar, Muhammad Shahid | - |
dc.date.accessioned | 2024-05-13T12:30:20Z | - |
dc.date.available | 2024-05-13T12:30:20Z | - |
dc.date.issued | 2024-02 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/91174 | - |
dc.description.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. | - |
dc.format.extent | 15 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma | - |
dc.type | Article | - |
dc.identifier.wosid | 001185074100001 | - |
dc.identifier.doi | 10.1109/ACCESS.2024.3369491 | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.12, pp 37557 - 37571 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85186086843 | - |
dc.citation.endPage | 37571 | - |
dc.citation.startPage | 37557 | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 12 | - |
dc.type.docType | Article | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | Tumors | - |
dc.subject.keywordAuthor | viral cancers | - |
dc.subject.keywordAuthor | artificial intelligence | - |
dc.subject.keywordAuthor | cancer diagnosis | - |
dc.subject.keywordAuthor | traditional cancer diagnostic | - |
dc.subject.keywordAuthor | Hepatocellular carcinoma (HCC) | - |
dc.subject.keywordPlus | LIVER-TUMOR DETECTION | - |
dc.subject.keywordPlus | HEPATITIS-B-VIRUS | - |
dc.subject.keywordPlus | TEXTURE ANALYSIS | - |
dc.subject.keywordPlus | HEALTH-CARE | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | IMAGES | - |
dc.subject.keywordPlus | EPIDEMIOLOGY | - |
dc.subject.keywordPlus | SURVEILLANCE | - |
dc.subject.keywordPlus | RADIOMICS | - |
dc.subject.keywordPlus | ANALYTICS | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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