Prediction of Heart Disease using Major Risk Factors based on ABC Optimized Neural Network

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.7 · Issue 3

Published

October 2018

Access

Open Access

Licence

CC BY-NC-SA 4.0

Priyanka Mandot Ajay Singh Dhabariya

This paper is particularly interested in the classification of data. The classification allows obtaining a prediction model from training data and test data. These data are screened by a classification algorithm that through the combination of mathematical tools and computer methods produces a new model capable of classified data possibly having the same classes of data.
The analysis of data in the field of medicine is becoming more frequent in order to clarify the diagnoses, to refine the research methods and to envisage appropriate supplies of equipment according to the importance of the pathologies that appear. To analyze the present data in order to predict optimal results. This paper aims to implement a framework for prediction of heart disease using major risk factors based on the Artificial Bee Colony (ABC) optimized Neural Network. Performance of proposed research work is evaluated using the true positive rate, false positive rate, accuracy, and specificity.

Artificial Bee Colony Cardiovascular disease MLP Neural Network RBF

Priyanka Mandot, Ajay Singh Dhabariya (2018). Prediction of Heart Disease using Major Risk Factors based on ABC Optimized Neural Network. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.7, Issue 3. ISSN: 2319-4863.

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