Volume 9, Number 2/3

Applying Neural Networks for Supervised Learning of Medical Data

  Authors

Ourida Ben Boubaker, Jouf University, Kingdom of Saudi Arabia

  Abstract

Constructing a classification model based on some given patterns is a form of learning from the environment perception. This modelling aims to discover new knowledge embedded in the input observations. Learning behaviour of the neural network model enhances the classification properties. This paper considers artificial neural networks for learning two different medical data sets in term of number of instances. The experiment results confirm that the back-propagation supervised learning algorithm has proved its efficiency for such non-linear classification issues.

  Keywords

Supervised learning, Artificial Neural Networks, Artificial intelligence, Learning, Classification