دورية أكاديمية

Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma

التفاصيل البيبلوغرافية
العنوان: Machine Learning Based Diagnostic Paradigm in Viral and Non-Viral Hepatocellular Carcinoma
المؤلفون: Arun Asif, Faheem Ahmed, Zeeshan, Javed Ali Khan, Eman Allogmani, Nora El Rashidy, Sobia Manzoor, Muhammad Shahid Anwar
المصدر: IEEE Access, Vol 12, Pp 37557-37571 (2024)
بيانات النشر: IEEE, 2024.
سنة النشر: 2024
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Hepatocellular carcinoma (HCC), viral cancers, artificial intelligence, cancer diagnosis, traditional cancer diagnostic, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2169-3536
Relation: https://ieeexplore.ieee.org/document/10444549/; https://doaj.org/toc/2169-3536
DOI: 10.1109/ACCESS.2024.3369491
URL الوصول: https://doaj.org/article/8087061b4fd9475fa65d26dffea25be1
رقم الأكسشن: edsdoj.8087061b4fd9475fa65d26dffea25be1
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21693536
DOI:10.1109/ACCESS.2024.3369491