<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Jin HK</submitter><funding>the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education</funding><funding>Chung-Ang University Graduate Research Scholarship in 2023</funding><pagination>1013</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11406751</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>24(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>ChatGPT, a recently developed artificial intelligence (AI) chatbot, has demonstrated improved performance in examinations in the medical field. However, thus far, an overall evaluation of the potential of ChatGPT models (ChatGPT-3.5 and GPT-4) in a variety of national health licensing examinations is lacking. This study aimed to provide a comprehensive assessment of the ChatGPT models' performance in national licensing examinations for medical, pharmacy, dentistry, and nursing research through a meta-analysis.&lt;h4>Methods&lt;/h4>Following the PRISMA protocol, full-text articles from MEDLINE/PubMed, EMBASE, ERIC, Cochrane Library, Web of Science, and key journals were reviewed from the time of ChatGPT's introduction to February 27, 2024. Studies were eligible if they evaluate</pubmed_abstract><journal>BMC medical education</journal><pubmed_title>Performance of ChatGPT-3.5 and GPT-4 in national licensing examinations for medicine, pharmacy, dentistry, and nursing: a systematic review and meta-analysis.</pubmed_title><pmcid>PMC11406751</pmcid><funding_grant_id>2021R1A6A1A03044296</funding_grant_id><pubmed_authors>Jin HK</pubmed_authors><pubmed_authors>Kim E</pubmed_authors><pubmed_authors>Lee HE</pubmed_authors></additional><is_claimable>false</is_claimable><name>Performance of ChatGPT-3.5 and GPT-4 in national licensing examinations for medicine, pharmacy, dentistry, and nursing: a systematic review and meta-analysis.</name><description>&lt;h4>Background&lt;/h4>ChatGPT, a recently developed artificial intelligence (AI) chatbot, has demonstrated improved performance in examinations in the medical field. However, thus far, an overall evaluation of the potential of ChatGPT models (ChatGPT-3.5 and GPT-4) in a variety of national health licensing examinations is lacking. This study aimed to provide a comprehensive assessment of the ChatGPT models' performance in national licensing examinations for medical, pharmacy, dentistry, and nursing research through a meta-analysis.&lt;h4>Methods&lt;/h4>Following the PRISMA protocol, full-text articles from MEDLINE/PubMed, EMBASE, ERIC, Cochrane Library, Web of Science, and key journals were reviewed from the time of ChatGPT's introduction to February 27, 2024. Studies were eligible if they evaluate</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Sep</publication><modification>2025-04-04T01:37:24.319Z</modification><creation>2025-04-04T01:37:24.319Z</creation></dates><accession>S-EPMC11406751</accession><cross_references><pubmed>39285377</pubmed><doi>10.1186/s12909-024-05944-8</doi></cross_references></HashMap>