• S Prabhavathi
• Dr. P Sumathi
• K Narayana Prakash
• G karthikeyan
• M JAGADEESH

Personal health record has emerged as a patient-centric model of health information exchange. To ensure patient-centric control over their own diabetic symptoms analyze statistics are framed, which is essential to have fine-grained data access control mechanisms that scrutinize the performance of diabetic system. Different type of algorithms is framed to create the cluster of record based on the medical history of the diabetic patients. The data set is mined to analyze the symptoms and the un-necessary data are pruned to create a valid set. A disease, if predicted wrongly, there may not be any chance of curing it. With the advancement of computing facility provided by information technology, it is now possible to predict many conditions of ailments more accurately. The first big advantage of information technology is that a huge data storage of past patient’s records are maintained and monitored by hospitals continuously. The stored medical data can be helpful to doctors to examine patterns in the data set. The patterns found in data sets may be used for clinical diagnosis. Clustering and Genetic Algorithms are quite suitable for pattern analyses. The principal objective of clustering computation was to find different groups of diabetes patients with similar symptoms within a group but different symptoms of other groups. The classification was performed based on selected training parameters

PHR - Personal health record, GA- Genetic Algorithm

"DIABETIC DIAGNOSIS WITH DATA ANALYTICS IN NEURAL FRAMWORK WITH MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.7-12, April-2021, Available :http://www.jetir.org/papers/JETIRER06002.pdf

"DIABETIC DIAGNOSIS WITH DATA ANALYTICS IN NEURAL FRAMWORK WITH MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp7-12, April-2021, Available at : http://www.jetir.org/papers/JETIRER06002.pdf