AI Medical Compendium Journal:
Transfusion

Showing 1 to 8 of 8 articles

O blood usage trends in the pediatric population 2015-2019: A multi-institutional analysis.

Transfusion
BACKGROUND: In 2019, AABB released the bulletin "Recommendations on the Use of Group O Red Blood Cells" in which the recommendations about pediatric and neonatal blood transfusions were limited. Eight U.S. pediatric hospitals sought to determine tren...

Privacy-preserving federated data access and federated learning: Improved data sharing and AI model development in transfusion medicine.

Transfusion
BACKGROUND: Health data comprise data from different aspects of healthcare including administrative, digital health, and research-oriented data. Together, health data contribute to and inform healthcare operations, patient care, and research. Integra...

A deep learning approach to prediction of blood group antigens from genomic data.

Transfusion
BACKGROUND: Deep learning methods are revolutionizing natural science. In this study, we aim to apply such techniques to develop blood type prediction models based on cheap to analyze and easily scalable screening array genotyping platforms.

Classification of posttransfusion adverse events using a publicly available artificial intelligence system.

Transfusion
BACKGROUND: Correct classification of transfusion reactions is important not only for effective patient care and donor management but also for accurate tracking of events in hemovigilance systems. We compared the ability of a generative artificial in...

An unsupervised learning approach to identify immunoglobulin utilization patterns using electronic health records.

Transfusion
BACKGROUND: Managing Canada's immunoglobulin (Ig) product resource allocation is challenging due to increasing demand, high expenditure, and global shortages. Detection of groups with high utilization rates can help with resource planning for Ig prod...

Transfusion-associated hyperkalemia in pediatric population: Analyses for risk factors and recommendations.

Transfusion
BACKGROUND: Transfusion-associated hyperkalemia (TAH) is a potentially life-threatening complication of red blood cell (RBC) transfusion. Previously, we reported features of RBC transfusions from 35 pediatric patients (TAH group) who had hyperkalemia...

Machine learning-based prediction of transfusion.

Transfusion
BACKGROUND: The ability to predict transfusions arising during hospital admission might enable economized blood supply management and might furthermore increase patient safety by ensuring a sufficient stock of red blood cells (RBCs) for a specific pa...