Using different types of neural networks in detection the body's readiness for blood donation and determining the value of each of its parameters using genetic algorithm

Authors

  • Zahra Jafari Islamic Azad University
  • Asma Mahdavi Yousefi Islamic Azad University
  • Saman Rajabi Seraj Higher Education Institute

DOI:

https://doi.org/10.15649/2346075X.998

Keywords:

Perceptron neural network, RBF neural network, blood transfusion, Fisher’s discrimination ratio, genetic algorithm

Abstract

Blood transfusion is of great importance in the medical field, as blood donation centers are responsible for collecting and distributing blood and blood products. Artificial neural network is a data processing system getting ideas from the human brain and designs a data structure that acts like a neuron using programming science and by creating a network between these neurons and combining large amounts of data with smart algorithms and their rapid processing, the network is trained. In this study, data is extracted from the blood transfusion service center and the perceptron neural network, RBF neural network, Fisher’s discrimination ratio and genetic algorithm were examined, and finally the highest possible accuracy from the neural network was achieved.

Author Biographies

  • Zahra Jafari, Islamic Azad University
    Department of Medical Engineering, Faculty of Electrical Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
  • Asma Mahdavi Yousefi, Islamic Azad University

    Department of Medical Engineering, Faculty of Electrical Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

  • Saman Rajabi, Seraj Higher Education Institute

    Assistant Professor of Electrical Engineering Department, Seraj Higher Education Institute, Tabriz, Iran

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Issue

Section

Original research and innovation article

Published

2020-12-01

How to Cite

Jafari, Z., Mahdavi Yousefi, A., & Rajabi, S. (2020). Using different types of neural networks in detection the body’s readiness for blood donation and determining the value of each of its parameters using genetic algorithm. Innovaciencia, 8(1), 1-10. https://doi.org/10.15649/2346075X.998

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