{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Coelho H"],"funding":["Fundação para a Ciência e Tecnologia"],"pagination":["8479"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12693012"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(23)"],"pubmed_abstract":["<b>Background</b>: Patient blood management (PBM) is a patient-centered, evidence-based approach for optimizing anemia management, minimizing blood loss, and ensuring appropriate transfusion. Artificial intelligence (AI) provides powerful tools for prediction, diagnosis, and decision support across PBM, but current evidence remains emerging and not yet consolidated. <b>Objectives</b>: This review synthesizes AI applications in PBM, summarizing predictive, diagnostic, and decision support models; highlighting methodological trends; and discussing challenges for clinical translation. <b>Methods</b>: PubMed, Scopus, and Web of Science were searched from inception to 31 March 2025. Eligible studies reported AI models addressing the three established PBM pillars. Studies on transfusion safety a"],"journal":["Journal of clinical medicine"],"pubmed_title":["Artificial Intelligence in Patient Blood Management: A Systematic Review of Predictive, Diagnostic, and Decision Support Applications."],"pmcid":["PMC12693012"],"funding_grant_id":["UIDB/50016/2020"],"pubmed_authors":["Rodrigues PM","Correia M","Coelho H","Silva F"],"additional_accession":[]},"is_claimable":false,"name":"Artificial Intelligence in Patient Blood Management: A Systematic Review of Predictive, Diagnostic, and Decision Support Applications.","description":"<b>Background</b>: Patient blood management (PBM) is a patient-centered, evidence-based approach for optimizing anemia management, minimizing blood loss, and ensuring appropriate transfusion. Artificial intelligence (AI) provides powerful tools for prediction, diagnosis, and decision support across PBM, but current evidence remains emerging and not yet consolidated. <b>Objectives</b>: This review synthesizes AI applications in PBM, summarizing predictive, diagnostic, and decision support models; highlighting methodological trends; and discussing challenges for clinical translation. <b>Methods</b>: PubMed, Scopus, and Web of Science were searched from inception to 31 March 2025. Eligible studies reported AI models addressing the three established PBM pillars. Studies on transfusion safety a","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Nov","modification":"2026-05-26T14:05:53.547Z","creation":"2026-05-24T03:11:07.235Z"},"accession":"S-EPMC12693012","cross_references":{"pubmed":["41375782"],"doi":["10.3390/jcm14238479"]}}