Indian Journal of Science and Technology
DOI: 10.17485/ijst/2009/v2i8.5
Year: 2009, Volume: 2, Issue: 8, Pages: 32-34
Original Article
S. Djodilatchoumy1 , N. Rama2 and S. Gunasekaran3
1Dept. of Computer Sci. & Applications; 3 Spectrophysics Res. Lab., Pachaiyappa’s College, Chennai-600030, India.
2Dept. of Computer Science, Presidency College, Chennai-600005, India.
*Author for the correspondence:
S. Djodilatchoumy
Dept. of Computer Sci. & Applications
Pachaiyappa’s College, Chennai-600030, India
E-mail: [email protected]
Anaemia is a common problem in Chronic Kidney Disease (CKD) leading to substantial morbidity and mortality if untreated. The particular cells of the failing kidney are unable to secrete sufficient erythropoietin, the harmone that stimulates erythropoiesis. Treatment of anaemia with erythropoiesisstimulating agents (ESA) has led to increased quality of life and a reduced cardiovascular risk. Therefore anaemic blood has to be identified and proper treatment has to be given. Though investigations on characterisation of anaemic blood and therapeutic effect of erythropoietin in CKD have been done by many, not much work is done on automation of this investigations. The goal of this study is to train the System (Neural Network [NN]) to identify whether the given blood sample is anaemic blood or not and also to examine prospectively the effect of erythropoietin in anaemic patients using the System which is already trained to identify the anaemic blood.
Keywords: Anaemia, erythropoietin, chronic kidney disease, neural network.
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