Artificial immune recognition systems in medical diagnosis

Medical diagnosis is an exciting are of research and many researchers have been working on the application of Artificial Intelligence techniques to develop disease recognition systems. They are analysing currently available information and also biochemical data collecting from clinical laboratories and experts for identifying pathological status of the patient. During the process of diagnosis, the clinical data so obtained from several sources must be inferred and classified into a particular pathology. Computer aided diagnosis tools designed based on biologically inspired methods such as artificial neural/immune networks can be employed to improve the regular diagnostic process and to avoid misdiagnosis. In this paper pre-processing and classification techniques are used to train the system. Artificial immune recognition method is used for pre-processing and KNN classifier is used for classification. The system is tested with some sample data and obtained the results. The system is validated with annotated data.