Читать книгу Data Analytics in Bioinformatics - Группа авторов - Страница 60

Vrs Jhalia ¹ * and Tripti Swarnkar ²

¹ Department of Computer Science and Engineering, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, India

² Department of Computer Application, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, India

Abstract

Proper diagnosis of disease requires deep analysis and classification of disease. In the last two decades the exponential increase in the biological data emerged as an opportunity for many researchers. “Bioinformatics” is the integration of biology and computer science to develop methods and software tools for understanding this large biological dataset. Analyzing the hunks of data by manual means is difficult. Here computer science plays a pivotal role for extracting the hidden patterns. Among all Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) is considered as the most efficient model in pattern recognition by an automated process. ANN is a type of data structure inspired by networks of biological neurons organized in layers, in which data set is fed to the model, model learns the features from the input and predicts the output. The performance is compared based on classification accuracy. In this chapter we will make a review by comparing the classification accuracy of the ANN model with other existing classification model to get more insights to draw hypothesis.

Keywords: Machine learning (ML), artificial neural network (ANN), prediction model, disease classification