Neural Network and Artificial Immune Algori- thms for the Classification of Medical Data Series

Abstract

This paper describes the applicability of artificial immune
algorithms. Medical data series classification technique by Artifi-
cial Immune Algorithm is used for Neural Network Algorithm
input data definitions. Artificial Immune Algorithms is created and
trained for the purpose of Arterial Blood Gas parameters classifica-
tion: pH, PaCO2, PaO2, HCO3. The main goal of this paper is to
develop a artificial neural network technique for Arterial Blood
Gases short-term prediction. The main question that is considered is
how to predict some dynamic parameters that describe blood gases
nature. A model of a physical system has an error associated with its
predictions due to the dependences of the physical systems output
on uncontrollable and unobservable quantities. The use of artifi-
cial methods creates the possibilities of obtaining some parameter
values on the proper level of probability. This would provide a di-
rect feedback to the clinical staff about the progress of a patient, the
success of individual treatments, and quality of care as well as pre-
dicting blood gas value.