<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>105(3)</volume><submitter>Gui Y</submitter><funding>Guangxi Natural Science Foundation</funding><funding>Self-financing Scientific Research Subject of Guangxi Health Department</funding><funding>Open Project of NHC Key Laboratory of Thalassemia Medicine</funding><journal>Annals of hematology</journal><pagination>112</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12904909</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Machine learning and AI-Assisted red blood cell morphology analysis for effective thalassemia screening.</pubmed_title><pmcid>PMC12904909</pmcid><funding_grant_id>Z-A20220420</funding_grant_id><funding_grant_id>2023GXNSFDA026058</funding_grant_id><funding_grant_id>GJWJWDP202210</funding_grant_id><pubmed_authors>Zhang F</pubmed_authors><pubmed_authors>Chen W</pubmed_authors><pubmed_authors>Liu Q</pubmed_authors><pubmed_authors>Gui Y</pubmed_authors><pubmed_authors>Su Y</pubmed_authors><pubmed_authors>Zhao J</pubmed_authors><pubmed_authors>Qin C</pubmed_authors></additional><is_claimable>false</is_claimable><name>Machine learning and AI-Assisted red blood cell morphology analysis for effective thalassemia screening.</name><description/><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Feb</publication><modification>2026-07-09T12:26:57.99Z</modification><creation>2026-07-09T11:17:41.874Z</creation></dates><accession>S-EPMC12904909</accession><cross_references><pubmed>41686242</pubmed><doi>10.1007/s00277-026-06860-1</doi></cross_references></HashMap>