Artificial Intelligence In Transfusion Medicine: A Contemporary Review

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Authors: Neha Singh
Cited by: 0

Abstract

Artificial intelligence (AI)-including machine learning (ML), deep learning (DL), and natural language processing (NLP)-is transforming transfusion medicine (TM) across the donor-to-recipient continuum.This review synthesizes applications in donor recruitment-motivation and mobilization, donor screening, laboratory microbiology and immunohematology, component quality assessment, inventory forecasting, clinical decision support and patient blood management (PBM), and hemovigilance.We summarize reported benefits, implementation pitfalls, regulatory and ethical considerations, and pragmatic steps to deploy AI safely.Across domains, AI shows promise to improve safety, reduce wastage, and personalize care; however, rigorous prospective evaluation, calibration, transparency, and human-in-the-loop governance remain essential.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Blood donation and transfusion practices Blood transfusion and management

Publication details

Journal / source
Journal of Clinical Transplantation
Publication date
25 February 2026
Language
EN