Artificial immune system in risk of falling classification

Abstract

Human immune system has been an inspiration for the fields of computer science, engineering and medicine. Over the last few years, there has been an ever increasing development in the area of artificial immune systems. Risk of falling is one of the most important risks in medicine and quality patient care. Patient classification criteria for the risk of falling are measured by the Morse scale. This paper deals with classification of artificial immune system for patient's risk of falling. A simple implementation and suitable visualization technique based on principal component analysis and clonal selection algorithm are described here. This research was conducted on patients and collected data set from The Institute of Neurology, Clinical centre of Vojvodina. © 2011 IEEE.