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Assessment of Cognitive Level for Alzheimer's Using Neural Networks

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3 Author(s)
Srivaramangai Ramanujam ; Dept. of Inf. Technol., Univ. of Mumbai, Mumbai, India ; Nilendu Purohit ; Nainish Bhoir

The paper introduces two neural network techniques to compare and analyze the detection level of Alzheimer's disease in a patient. The proposed module uses a Neurological Memory test named Mini Mental Status Examination (MMSE). It is authorized to be used only by neurologist, neuropsychologist and psychiatrist for determining the cognitive level. Doctors use the score of MMSE to evaluate the cognitive level of the patient. According to the method used here, the score below 21 indicates low cognitive level. It uses two Neural Network techniques namely Single Layer Perceptron and Multilayer Feed Forward Perceptron Algorithm. It analyzes each input from the MMSE test and intelligently screens whether the patient is normal or with low Cognitive level thereby reducing the considerable load of doctors or evaluators. The MMSE score also gives an idea to the examiner whether further detailed clinical examination of patients for Alzheimer's disease is required or not.

Published in:

2011 Second International Conference on Intelligent Systems, Modelling and Simulation

Date of Conference:

25-27 Jan. 2011