Upper Stomach Disorder Detection System using Backpropagation Artificial Neural Network

Abstract

The study aims to make simple detection of upper stomach disorders of the iris image based on the chart to iridology, making an upper stomach disorder detection system using backpropagation artificial neural network method and determining the accuracy of the system. Backpropagation artificial neural networks is a type of neural network that trains the network to get a balance between the network's ability to recognize patterns used during training as well as networking capabilities to provide a correct response to similar input patterns but not identical with patterns during training. Iridology is the science of analyzing the subtle structures of the iris. This research was conducted from the shooting stage of the eye image using the camera, data obtained as 40 iris images. Detection of disorders using chart to iridology from the iris imagery data of 20 pairs of eyes consisting of left and right. This results of 10 pairs of eye image showed that upper stomach disorder and 10 pairs of eye image showed no upper stomach disorder.

The Patient Organism Modeling for Diagnosis with the Usage of a Multi Agent Representation

“…Problems of human disease medical diagnosis are very difficult. But now there is an opportunity to use the achievements of artificial intelligence (AI) to obtain a timely and better diagnosis of human disease [1]- [5]. It is through the use of models based on multi-agent representation that we have the opportunity to formulate a qualitative paradigm for building a model of medical thinking for diagnosis.…”