Author(s): Mehrdad Payandeh | Mehrnoush Aeinfar | Vahid Aeinfar | Mohsen Hayati
Journal: International Journal of Hematology-Oncology and Stem Cell Research
ISSN 2008-3009
Volume: 3;
Issue: 4;
Start page: 25;
Date: 2009;
Original page
Keywords: Artificial Neural Network | Multilayer Perceptron (MLP) | Multi-Variable Non-linear Regression | Blood
ABSTRACT
"nAbstract: This paper represents a novel use of artificial neural networks in medical science. The proposed technique involves training a Multi Layer Perceptron (MLP) (a kind of artificial neural network) with a BP learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from H1 machine. The blood test parameters and diagnosis of physician about the diseases of 450 patients from Taleghani Hospital in Kermanshah, Iran, are used in a supervised training method to update network parameters. This method was implemented to diagnose these disorder and cancer: Megaloblastic Anaemia, Thalassemia, Idiopathic thrombocytopenic pupura (ITP), Chronic myelogenous leukemia and Lymphoproliferative.
Journal: International Journal of Hematology-Oncology and Stem Cell Research
ISSN 2008-3009
Volume: 3;
Issue: 4;
Start page: 25;
Date: 2009;
Original page
Keywords: Artificial Neural Network | Multilayer Perceptron (MLP) | Multi-Variable Non-linear Regression | Blood
ABSTRACT
"nAbstract: This paper represents a novel use of artificial neural networks in medical science. The proposed technique involves training a Multi Layer Perceptron (MLP) (a kind of artificial neural network) with a BP learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from H1 machine. The blood test parameters and diagnosis of physician about the diseases of 450 patients from Taleghani Hospital in Kermanshah, Iran, are used in a supervised training method to update network parameters. This method was implemented to diagnose these disorder and cancer: Megaloblastic Anaemia, Thalassemia, Idiopathic thrombocytopenic pupura (ITP), Chronic myelogenous leukemia and Lymphoproliferative.
