{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["11(21)"],"submitter":["Martinino A"],"pubmed_abstract":["Hepatocellular carcinoma ranks fifth amongst the most common malignancies and is the third most common cause of cancer-related death globally. Artificial Intelligence is a rapidly growing field of interest. Following the PRISMA reporting guidelines, we conducted a systematic review to retrieve articles reporting the application of AI in HCC detection and characterization. A total of 27 articles were included and analyzed with our composite score for the evaluation of the quality of the publications. The contingency table reported a statistically significant constant improvement over the years of the total quality score (<i>p</i> = 0.004). Different AI methods have been adopted in the included articles correlated with 19 articles studying CT (41.30%), 20 studying US (43.47%), and 7 studying"],"journal":["Journal of clinical medicine"],"pagination":["6368"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9655417"],"repository":["biostudies-literature"],"pubmed_title":["Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review."],"pmcid":["PMC9655417"],"pubmed_authors":["Annunziata S","Aloulou M","Kirchgesner TP","Singhal S","Patel T","Giovinazzo F","Chatterjee S","Scarano Pereira JP","Agnes S","Treglia G","Martinino A"],"additional_accession":[]},"is_claimable":false,"name":"Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review.","description":"Hepatocellular carcinoma ranks fifth amongst the most common malignancies and is the third most common cause of cancer-related death globally. Artificial Intelligence is a rapidly growing field of interest. Following the PRISMA reporting guidelines, we conducted a systematic review to retrieve articles reporting the application of AI in HCC detection and characterization. A total of 27 articles were included and analyzed with our composite score for the evaluation of the quality of the publications. The contingency table reported a statistically significant constant improvement over the years of the total quality score (<i>p</i> = 0.004). Different AI methods have been adopted in the included articles correlated with 19 articles studying CT (41.30%), 20 studying US (43.47%), and 7 studying","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Oct","modification":"2025-04-25T23:41:16.614Z","creation":"2025-04-06T09:25:56.597Z"},"accession":"S-EPMC9655417","cross_references":{"pubmed":["36362596"],"doi":["10.3390/jcm11216368"]}}