Abstract:
The main emphasize of paper is the
classification of Acute upper Gastrointestinal
Bleeding based on Rough neural network.
Classification is used to extract model describing
important and data classes or future data trends. A
conventional neural network consists of several
layers of neurons. Each neuron receives input from
other neurons and external environment and
produces output. A rough neural network consists of
conventional neurons and rough neurons connected
to each other. A rough neuron can be viewed as a
pair of neurons, one for the upper bound and the
other for the lower bound. Rough neural network
consists of one input layer, one output layer and one
hidden layer. The system can classify 7 types of
classes for acute upper gastrointestinal bleeding.
This system is implemented by using Java
programming language.
