• Suramya S
• Srinivasachar G

Diabetes Mellitus is one of the diseases that cannot be transferred from one person to another and has great impact on human life today. Due to the lifestyle and work schedule changes in the recent times, India houses lots of diabetic people in it. There are many other disorders connected to diabetes mellitus hence treating it in an early stage is very much necessary. The health care systems generate a large amount of data in less time, and these data can be both structured and unstructured. The main task here is to store, manage and analyze this data. Hence, big data analytics is used for enhanced insight, predictions about developing other disorders in the near future and also improves health care system by reducing the execution time and the optimal cost. The goal of this paper is to detect if a person would develop diabetes in future so that it can be obstructed or at least push it further for a few years. To do this we use Logistic Regression Statistical Model which minimizes the classification error. As there is a saying, “Prevention is better than Cure”, so providing an alert regarding their vulnerability towards a specific medication is always helpful.

Diabetes, Big Data, Regression, Healthcare System, Statistical Model

"Diabetes Detection using Big Data Analytics with Logistic Regression Model ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 1, page no.170-172, January 2020, Available :http://www.jetir.org/papers/JETIR1908965.pdf

"Diabetes Detection using Big Data Analytics with Logistic Regression Model ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 1, page no. pp170-172, January 2020, Available at : http://www.jetir.org/papers/JETIR1908965.pdf