Software aided diagnosing of diseases using RBF based neural networks [RADD]

With the advancement in technology and change in lifestyle, Indians are more prone to various disorders like diabetes, stroke, hypertension, etc. Presence of these diseases is identified only by regular monitoring and invasive blood tests. Though there is much successful management of communicable diseases and genetic disorders after they occur, there are only limited procedures to identify before they occur. A procedure, which detects the occurrence of such lifetime disorders would save the livelihood, before reaching the critical stage, is essential. The occurrence of such diseases can be detected by inherent watch of symptoms caused in existing patients. The similarity between the existing patients is monitored by using a FUNAP [Function Approximation] System. Existing patients’ data are collected and the system is trained to detect the diseases of monitoring new patients. The method is efficient as it uses artificial neural network for matching and it can be tuned according to the requirements. The system is explained with its architecture and its performance is compared with existing methods.