Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation

Authors

  • Tamer A. Addissouky Department of Biochemistry, Science Faculty, Menoufia University, Menoufia; Al-Hadi University College, Baghdad, Iraq; MLS ASCP, United States; MLS Ministry of Health, Alexandria, Egypt https://orcid.org/0000-0003-3797-9155
  • Majeed M. A. Ali Al-Hadi University College, Baghdad, Iraq
  • Ibrahim El Tantawy El Sayed Department of Biochemistry, Science Faculty, Menoufia University, Menoufia, Egypt
  • Mahmood Hasen Shuhata Alubiady Al-Hadi University College, Baghdad, Iraq

DOI:

https://doi.org/10.15575/join.v9i1.1297

Keywords:

Artificial Intelligence, Deep Learning, Imaging, Machine Learning, Hepatocellular carcinoma

Abstract

This study aims to provide an overview of the current state-of-the-art applications of artificial intelligence (AI) and machine learning in the management of hepatocellular carcinoma (HCC), and to explore future directions for continued progress in this emerging field.  This study is a comprehensive literature review that synthesizes recent findings and advancements in the application of AI and machine learning techniques across various aspects of HCC care, including screening and early detection, diagnosis and staging, prognostic modeling, treatment planning, interventional guidance, and monitoring of treatment response. The review draws upon a wide range of published research studies, focusing on the integration of AI and machine learning with diverse data sources, such as medical imaging, clinical data, genomics, and other multimodal information.  The results demonstrate that AI-based systems have shown promise in improving the accuracy and efficiency of HCC screening, diagnosis, and tumor characterization compared to traditional methods. Machine learning models integrating clinical, imaging, and genomic data have outperformed conventional staging systems in predicting survival and recurrence risk. AI-based recommendation systems have the potential to optimize personalized therapy selection, while augmented reality techniques can guide interventional procedures in real-time. Moreover, longitudinal application of AI may enhance the assessment of treatment response and recurrence monitoring. Despite these promising findings, the review highlights the need for rigorous multicenter prospective validation studies, standardized multimodal datasets, and thoughtful consideration of ethical implications before widespread clinical implementation of AI technologies in HCC management.

Author Biography

Tamer A. Addissouky , Department of Biochemistry, Science Faculty, Menoufia University, Menoufia; Al-Hadi University College, Baghdad, Iraq; MLS ASCP, United States; MLS Ministry of Health, Alexandria

Al-Hadi University College, Baghdad, Iraq. Department of Biochemistry, Science Faculty, Menoufia University, Menoufia, Egypt MLS ministry of health, Alexandria, Egypt. MLS ASCP, United States Corresponding Author: Tamer A. Addissouky, Al-HADI University College, Baghdad. Iraq. - Department of Biochemistry, Science Faculty, Menoufia University, Egypt. - MLS ministry of health, Alexandria, Egypt.  - MLS, ASCP, USA.    Email:  tedesoky@gmail.com; tedesoky@science.menofia.edu.eg; https://orcid.org/0000-0003-3797-9155      

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