International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 5 Issue: 6 363 – 367 _______________________________________________________________________________________________ 363 IJRITCC | June 2017, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Enhancing Accuracy of Disease Prediction of KNN and Euclidean Distance using Hybrid Approach Amandeep Kaur ,Varinder Kaur Attri College Name:GNDU,RC Jalandhar (Department computer science) Postal Address: vill-kohala,potarsikka,the-baba bakala,disttAmritsar,Punjab Pin code- 143116 Mobile no: 8728807357 Email: sangharamandeep55@gmail.com Abstract:- Health monitoring is critical issue associated with now day lifestyle. Lack of time is causing serious issues corresponding to health. Proposed literature focus on this key aspect and provide mechanism to generate accurate predictions corresponding to parameters fetched from dataset. Hybrid approach of K Nearest neighbour and Euclidean distance is used for enhancement in health prediction. For demonstration dataset derived from UCI is utilized. Simulation results suggest considerable improvement over KNN and Euclidean distance mechanism during prediction. Keywords:- Health Monitoring, Prediction, dataset, K nearest neighbour, Euclidean distance, UCI __________________________________________________*****_________________________________________________ INTRODUCTION Our health care system is literally losing patients killing more and saving less. Enormous reasons for this gigantic problem exist. Most prominent reason is lack of time causing disease to spread without noticing. Hence when the disease is detected it is beyond the scope of cure. This paper describes models which are utilized to enhance health care environment as introduction, parameters utilized in each in the next section, highlight pros and cons in next section and then comprehensive comparison of techniques in last section. Techniques has been created and utilized to minimize the problem in hand. One of the techniques is personal health care monitoring and emergency response system. Personal health care system earlier relies on emergency phone call system. The service agent built a call service center at one side. This system generally deals with old age persons by providing them with telephone with special keys. In emergency user just need to press that emergency key and call to doctors and related persons is made. This system is efficient enough to handle problems of fertile old aged persons. The enhancement to Personnel health care system is also made by including speech recognition. According to emergency response team Personal Health care system requires four essential components. 1. The Membership Functions including Ids of valid participant utilizing the applications provided through personal health care system. 2. Hot line allowing users to connect with medical associates. 3. Contact list should be present where call can be placed in case of emergency 4. Database containing information about doctors and medical personals. (1) Resource requirements associated with users are enhancing day by day. It is not possible to provide such massive resource requirements though standalone physical machine. Technology is enhancing day by day. One product of technology is cloud computing. Cloud computing can be utilized to provide resources to the user which are earlier beyond the reach of user with stand alone physical machine. The proposed literature tackles following objectives 1. Analyze techniques of data mining used to predict diseases. 2. Improving performance of prediction by hybridizing KNN and Euclidean distance. 3. Minimizing Error rate in prediction. 4. Increasing accuracy of prediction. Next Section describes the utilization of various Data mining mechanisms in disease prediction. LITERATURE SURVEY This section describes existing mechanisms like KNN, Euclidean distance and ARIMA model. The proposed approach is described after words. Data Mining Approach for Liver Injury Detection (2)Age-contrasts in the recurrence and signs of medication incited liver damage are not completely portrayed.