Abstract: According to the World Health Organization, around 1.5 million people worldwide died due to diabetes in 2019. It is estimated that approximately 462 million people live with diabetes around the globe. According to other sources, about 432 million people worldwide have diabetes, the bulk living in low-and middle-income countries, and 1.5 million deaths are directly related to the disease diabetes annually. The amount of cases, morbidity and mortality rates in a specific time period or over time to time, the diabetes is steadily increasing over the past few decades. No doubt, Diabetes mellitus is a leading cause of deaths world wide and reduced life expectancy. This disease can be curable with early diagnosis and proper treatment. The purpose of this paper is to establish some predictive models using Machine Learning algorithms by taking a real time Diabetes mellitus dataset. In this paper, we have shown some real-time experiments and observations with the help of some Machine Learning algorithms, and also shown a clear picture on the predictive analysis for the detection of the disease Diabetes mellitus in medical science using Machine Learning algorithms using which patients may get accurate data so as to diagnose better for their early treatment.

Keywords: Algorithm, Classifier, Diabetes Mellitus, Machine Learning, Prediction.

PDF | DOI: 10.17148/IJARCCE.2021.101209

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