Usar diferentes tipos de redes neuronales para detectar la preparación del cuerpo para la donación de sangre y determinar el valor de cada uno de sus parámetros mediante un algoritmo genético

  • Zahra Jafari Islamic Azad University
  • Asma Mahdavi Yousefi Islamic Azad University
  • Saman Rajabi Seraj Higher Education Institute
Palabras clave: Perceptron neural network, RBF neural network, blood transfusion, Fisher’s discrimination ratio, genetic algorithm


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.

Biografía del autor/a

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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