An Approach to Diagnose Neurologic Disorder using Neuro Fuzzy Model

The major problem in medical field is todiagnose disease. Human beings always make mistakes and because of their limitation, diagnosis would give the major issue of human expertise. One of the most important problems of medical diagnosis, in general, is the subjectivity of the specialist. It can be noted, in particular in pattern recognition activities, that the experience of the professional is closely related to the final diagnosis. This is due to the fact that the result does not depend on a systematized solution but on the interpretation of the input symptoms from the patient. Almost all the physicians are challenged by the task of learning to predict. Hence, there is a need to solve the problem of deducing certain diseases or formulating a treatment based on more or less specified observations and knowledge. Here, a neuro fuzzy model is designed for diagnosis of Autistic Spectrum disorders which is a type of neurological disorder is proposed in this paper. The symptoms and signs are gathered and definitions of fuzzy membership values are defined. Feed forward multi layer network accepts those input fuzzy values and it is trained using back propagation training algorithm. Finally, the fruition of this process is compared with the expertise to know its performance.