Prediction of perioperative transfusions using an artificial neural network.

Journal: PloS one

PMID: 32092108

Abstract

BACKGROUND: Accurate prediction of operative transfusions is essential for resource allocation and identifying patients at risk of postoperative adverse events. This research examines the efficacy of using artificial neural networks (ANNs) to predict transfusions for all inpatient operations.

Authors

Steven Walczak

School of Information and Florida Center for Cybersecurity, University of South Florida, 4202 E. Fowler Ave., CIS 1040, Tampa, FL, 33620, USA. swalczak@usf.edu.
Vic Velanovich

Division of General Surgery, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.

Keywords

Age Factors Blood Transfusion Computer Simulation Databases, Factual Female Humans Machine Learning Male Neural Networks, Computer Perioperative Care Postoperative Hemorrhage Prognosis Risk Factors Sensitivity and Specificity Sex Factors

External Resources

View on PubMed Access via DOI PubMed (32092108)

Prediction of perioperative transfusions using an artificial neural network.

Abstract

Authors

Keywords

External Resources

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