• Plataforma de vídeos del IIT
  • Twitter
  • LinkedIn
  • Asociación de Ingenieros del ICAI
  • Intranet
  • Spanish
Go top
Paper information

Blood transfusion prediction using restricted Boltzmann machines

J. Cifuentes, Y. Yao, M. Yan, B. Zheng

Computer Methods in Biomechanics and Biomedical Engineering Vol. 23, nº. 9, pp. 510 - 517

Summary:

The availability of blood transfusion has been a recurrent concern for medical institutions and patients. Efficient management of this resource represents an important challenge for many hospitals. Likewise, rapid reaction during transfusion decisions and planning is a critical factor to maximize patient care. This paper proposes a novel strategy for predicting the blood transfusion need, based on available information, by means of Restricted Boltzmann Machines (RBM). By extracting and analyzing high-level features from 4831 patient records, RBM can deal with complex patterns recognition, helping supervised classifiers in the task of automatic identification of blood transfusion requirements. Results show that a successfully classification is obtained (96.85%), based only on available information from the patient records.


Keywords: Blood transfusion prediction; restricted Boltzmann machines; patterns recognition


JCR Impact Factor and WoS quartile: 1.763 - Q4 (2020)

DOI reference: DOI icon 10.1080/10255842.2020.1742709

Published on paper: July 2020.

Published on-line: March 2020.



Citation:
J. Cifuentes, Y. Yao, M. Yan, B. Zheng. Blood transfusion prediction using restricted Boltzmann machines. Computer Methods in Biomechanics and Biomedical Engineering. Vol. 23, nº. 9, pp. 510 - 517, July 2020. [Online: March 2020]


    Research topics:
  • Mathematical Models and Artificial Intelligence in Healthcare

pdf Preview
Request Request the document to be emailed to you.