Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation
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...
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Department of Informatics, UIN Sunan Gunung Djati Bandung
2024-04-01
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| Series: | JOIN: Jurnal Online Informatika |
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| Online Access: | https://join.if.uinsgd.ac.id/index.php/join/article/view/1297 |
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| author | Tamer Addissouky Majeed M. A. Ali Ibrahim El Tantawy El Sayed Mahmood Hasen Shuhata Alubiady |
| author_facet | Tamer Addissouky Majeed M. A. Ali Ibrahim El Tantawy El Sayed Mahmood Hasen Shuhata Alubiady |
| author_sort | Tamer Addissouky |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2b243115389644c98ac10708d807c8ff |
| institution | OA Journals |
| issn | 2528-1682 2527-9165 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | Department of Informatics, UIN Sunan Gunung Djati Bandung |
| record_format | Article |
| series | JOIN: Jurnal Online Informatika |
| spelling | doaj-art-2b243115389644c98ac10708d807c8ff2025-08-20T02:33:52ZengDepartment of Informatics, UIN Sunan Gunung Djati BandungJOIN: Jurnal Online Informatika2528-16822527-91652024-04-0191707910.15575/join.v9i1.12971340Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible TranslationTamer Addissouky0https://orcid.org/0000-0003-3797-9155Majeed M. A. Ali1Ibrahim El Tantawy El Sayed2Mahmood Hasen Shuhata Alubiady3Department of Biochemistry, Science Faculty, Menoufia University, Menoufia; Al-Hadi University College, Baghdad, Iraq; MLS ASCP, United States; MLS Ministry of Health, AlexandriaAl-Hadi University College, BaghdadDepartment of Biochemistry, Science Faculty, Menoufia University, MenoufiaAl-Hadi University College, BaghdadThis 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.https://join.if.uinsgd.ac.id/index.php/join/article/view/1297artificial intelligencedeep learningimagingmachine learninghepatocellular carcinoma |
| spellingShingle | Tamer Addissouky Majeed M. A. Ali Ibrahim El Tantawy El Sayed Mahmood Hasen Shuhata Alubiady Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation JOIN: Jurnal Online Informatika artificial intelligence deep learning imaging machine learning hepatocellular carcinoma |
| title | Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation |
| title_full | Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation |
| title_fullStr | Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation |
| title_full_unstemmed | Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation |
| title_short | Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation |
| title_sort | realizing the promise of artificial intelligence in hepatocellular carcinoma through opportunities and recommendations for responsible translation |
| topic | artificial intelligence deep learning imaging machine learning hepatocellular carcinoma |
| url | https://join.if.uinsgd.ac.id/index.php/join/article/view/1297 |
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