<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>11(21)</volume><submitter>Martinino A</submitter><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 (&lt;i>p&lt;/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</pubmed_abstract><journal>Journal of clinical medicine</journal><pagination>6368</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9655417</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review.</pubmed_title><pmcid>PMC9655417</pmcid><pubmed_authors>Annunziata S</pubmed_authors><pubmed_authors>Aloulou M</pubmed_authors><pubmed_authors>Kirchgesner TP</pubmed_authors><pubmed_authors>Singhal S</pubmed_authors><pubmed_authors>Patel T</pubmed_authors><pubmed_authors>Giovinazzo F</pubmed_authors><pubmed_authors>Chatterjee S</pubmed_authors><pubmed_authors>Scarano Pereira JP</pubmed_authors><pubmed_authors>Agnes S</pubmed_authors><pubmed_authors>Treglia G</pubmed_authors><pubmed_authors>Martinino A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review.</name><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 (&lt;i>p&lt;/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</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Oct</publication><modification>2025-04-25T23:41:16.614Z</modification><creation>2025-04-06T09:25:56.597Z</creation></dates><accession>S-EPMC9655417</accession><cross_references><pubmed>36362596</pubmed><doi>10.3390/jcm11216368</doi></cross_references></HashMap>