GUI Based Model for Stroke Prediction
Jeena R S1, Sukesh Kumar A2

1Jeena R S, Department of Electronics & Communication, College of Engineering, Trivandrum, (Kerala). India.
2Dr. Sukesh Kumar A, Associate Professor, Rajiv Gandhi Institute of Development Studies, Vellayambalam, Trivandrum (Kerala). India. 

Manuscript received on 15 February 2017 | Revised Manuscript received on 22 February 2017 | Manuscript Published on 28 February 2017 | PP: 123-125  | Volume-6 Issue-3, February 2017 | Retrieval Number: C4852026317/17©BEIESP
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Abstract: The innovations in the field of artificial intelligence have paved way to the development of tools for assisting physicians in disease diagnosis and prognosis. Stroke is a leading cause of disability in developing countries like India. Early diagnosis of stroke is required for reducing the mortality rate. Research shows that various physiological parameters carry vital information for the prediction of stroke. This research work focuses on the design of a graphical user interface (GUI) for the prediction of stroke using risk parameters. Data collected from International Stroke Trial database was successfully trained and tested using Support vector machine (SVM). The linear kernel of SVM gave an accuracy of 90 %. This work has been implemented in MATLAB which can be used to predict the probability of occurrence of stroke.
Keywords: Stroke, Graphical User Interface (GUI), Support Vector Machine (SVM)

Scope of the Article: Machine Design