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Designing an Artificial Neural Network Model for the Prediction of Thrombo-embolic Stroke
Shanthi Dhanushkodi, G.Sahoo , Saravanan Nallaperumal
Pages - 10 - 18     |    Revised - 20-02-2009     |    Published - 15-03-2009
Volume - 3   Issue - 1    |    Publication Date - February 2009  Table of Contents
Artificial Intelligence, BPN, Neural Network, Thrombo-embolic Stroke
Artificial Neural Networks (ANN) are established analytical methods in bio-medical research. They have repeatedly outperformed traditional tools for pattern recognition and clinical outcome prediction while assuring continued adoption and learning. Extensive research had confirmed the utility of ANN for the solution of clinical diagnosis and prognostic problems. In this paper, we propose an ANN model that is understandable, practicable and capable of achieving accurate prediction of Thrombo-embolic Stroke disease. This model assists the physicians in taking decisions in the stages of diagnosis, based on the output generated by the system.
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Mr. Shanthi Dhanushkodi
- India
Dr. G.Sahoo
Birla Institute of Technology - India
Dr. Saravanan Nallaperumal
Birla Institute of Technology - India