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ARTIFICIAL INTELLIGENCE APPLICATIONS IN BLOOD BANKS: PROCESS OPTIMIZATION, DEMAND PREDICTION AND IMPROVEMENT IN HEALTHCARE MANAGEMENT

  • Luis Fernando Garcés Giraldo
  • , Jerónimo Garcés Machado
  • , Diana Carolina Velasco Cardona
  • , Lucia Palacios Moya
  • , Alejandro Valencia-Arias
  • , Sebastián Cardona-Acevedo
  • , David Alberto García Arango

Research output: Contribution to journalOriginal Articlepeer-review

Abstract

Blood banks play a vital role in healthcare systems by ensuring the supply of safe, high-quality blood products. However, their management faces logistical challenges that impact operational efficiency and healthcare. Artificial intelligence is emerging as a strategic tool to optimise processes, anticipate demand and strengthen decision-making. However, its application in blood banks remains fragmented, with disparate studies and varied methodological approaches. This study aimed to identify the applications, benefits and challenges of using artificial intelligence in the management of blood banks, as well as technological developments in this area. To achieve this objective, a systematic review was conducted in accordance with the PRISMA 2020 guidelines, enabling the structured analysis of existing knowledge. The conclusions highlight the need to consolidate disciplined development and integrate technological advances with robust ethical frameworks, guiding future applications towards an efficient, inclusive and sustainable health ecosystem.

Original languageAmerican English
Pages (from-to)940-954
Number of pages15
JournalScientific Culture
Volume11
Issue number3.1
DOIs
StateIndexed - 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025, University of AEGEAN. All rights reserved.

Keywords

  • Artificial Intelligence
  • Blood Banks
  • Demand Forecasting
  • Healthcare Management
  • Process Optimisation

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