Research paper on diabetic data analysis



Diabetic Data Analysis is a field of research which comes under analytics. Analytics is a subject of statistics to the extent that we read raw data by using computational techniques and then we make sense out of this raw data this is called analysis. An essential function in data mining and analytics is the Data Classification. A machine learning tool known as neural network is capable to perform various tasks in diabetic data analysis. Today, healthcare industries having large amount of data and to access that data analysis process is required, so there arise many complexities. Medicare industries face different kind of challenges, so it is very important to develop data analytics. In this paper an integrated approach is used to predict diabetes from neural network. Neural network can be taken as ubiquitous indicator. From various resources raw data has been collected and compare it to a tool that can be a trained machine for the prediction of diabetes patients. Main aim of integrating approach in neural network is to increase the accurate results in the prediction of diabetic patients. Big data is an approach to resolve the problem in an enhanced manner. A modeling structure is used in this paper.


Neural network, big data, data classification, diabetic data analysis, data mining, modeling.

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