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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/dspace/handle/123456789/7304

Title: Early diagnosis of Ischemia Stroke using neural network
Authors: Anita, Thakur
Surekha, Bhanot
Mishra, S.N.
???metadata.dc.contributor.url???: anni.thakur@gmail.com
Keywords: Feed forward neural network;MATLAB;Cerebral ischemia stroke;Neural networks (Computer science);Intelligent systems;Ischemia Stroke -- Diagnosis;Biomedical engineering
Issue Date: 11-Oct-2009
Publisher: Universiti Malaysia Perlis
Citation: p.2B10 1 - 2B10 5
Series/Report no.: Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009)
Abstract: Technological and computing evolution promoted new opportunities to improve the quality of life, in particular, the quality of early detection of acute disease. Many intelligent systems have been developed with the purpose of enhancing health-care and providing better health care facilities at reduced cost. Artificial Intelligent techniques are indeed worth exploring and integrating in the medical system for diagnosis, prediction and prescription. The aim of this paper is to determine a noninvasive method that the general population can easily use to detect whether a patient has cerebral ischemia stroke. The problem addressed in this paper is prediction of possibility of cerebral ischemia and it is estimated from symptoms and risk factors given by the patients. Exactly early prognosis of cerebral ischemia stroke has practical importance in medicine. A feed forward neural network with back propagation was used for decision of cerebral ischemia stroke prediction. Developed Neural network model with appropriate training provides an accuracy of 99.99%.
Description: Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.
URI: http://hdl.handle.net/123456789/7304
Appears in Collections:Conference Papers

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