SELF-DIAGNOSIS OF DIABETES USING CASE-BASED REASONING

Abstract

The continuously rising cost of medical spending, population size is growing up and increasing their need for healthcare, which requires time saving for laboratory technicians at the examination is a great incentive to create a new approach that helps to provide health care to patients at lower costs with good management. We focus on design an autonomic environment to help management of healthcare service. We started to apply the concept of the autonomic system that let the system work without intervention of the user. It has given by implemented and designed Case-Based Reasoning (CBR) algorithm in suitable way. we have proposed method can diagnose new patients according to the similar solution of stored cases. The system appears in attractive vision because the doctor just enters some parameters for new patient through the form of the system and the prediction result coming soon. The experimental results suggest that such a system is valuable both for less experienced clinicians and for experts where the system may function as a second option. The success of this work will permit to leverage the development of CBR systems in medicine. It will become possible to develop a web service to federate the CBR process across several domains of medicine. Finally our application can be extended by developing a special method to diagnose diabetes mellitus for gestational women and it can be implemented as a mobile application due to the development of technology nowadays