Work

Revolutionizing Blood Bank Management: Leveraging Machine Learning for Inventory Optimization and Shortage Prediction

Year: 2025

Type: article

Abstract: This study proposes a novel machine learning framework to enhance blood bank management, focusing on inventory optimization and shortage prediction. By leveraging big data analytics, the model identifies donor trends, seasonal fluctuations, and real-time hospital demand to dynamically adjust blood supply. The predictive accuracy of our machine learning model surpasses traditional heuristic approaches, ensuring timely blood availability while minimizing wastage. These findings offer a transformative step toward data-driven healthcare logistics, with direct implications for global blood supply chain efficiency.

Source: Asian Journal of Current Research

DOI: 10.56557/ajocr/2025/v10i29246

Authors: Ajit Pal Singh, Riya Pandey, Rahul Saxena, Suyash Saxena

Institutions: Sharda University, Government Institute of Medical Sciences, Greater Noida

Language: English

Topic: Blood donation and transfusion practices

Subfield: Management of Technology and Innovation

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4409388275

FWCI: 2.446

Cites:

Cited by: 2

Related to: 10