Suitability of neural network for disease prediction: a comprehensive literature review

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Suitability of neural network for disease prediction: a comprehensive literature review

Sharma Usha

Author Affiliations

¹MATS University, Raipur, Chhattisgarh, India

Res. J. Computer & IT Sci., Volume 5, Issue (6), Pages 12-20, August,20 (2017)

Abstract

In this study, suitability and appropriateness of neural network for prediction of disease by past recorded data is identified from a comprehensive literature review. Wherein, research contributions from 1991 to 2016 are reviewed. It is found that different various architecture of Artificial Neural Network (ANN) such as Back-Propagation Network (BPN), Radial Basis Faction (RBF), Support Vector Machine (SVM), Multi Layer Perception (MLP), and Recurrence Neural Network (RNN) are found appropriate and sufficiently suitable. In recent years, these architectures are found suitable for prediction of more than 100 diseases. The discussions of these architectures and their suitability, appropriateness for disease prediction is presented through this review article.

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