Prediction of Diabetics based on Machine Learning


Authors : Gayatri Tatikonda; Geethika Mannam; Jothsna Bhavani Tirumalasetty

Volume/Issue : Volume 7 - 2022, Issue 6 - June

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3u2xhiY

DOI : https://doi.org/10.5281/zenodo.6736737

Abstract : Diabetes is a chronic disease that occurs when the blood sugar levels of a human are high. When we ate, body turns the food into sugar(glucose). Big Data Analytics plays important role in the care industries. It can help in identifying the right treatment for people with diabetes. Care industries have massive volume of databases. Kidneys are mainly damaged by the diseases called diabetes damage, blindness, heart failure. Normally pancreas is supposed to release insulin. The future scientific field in the course of data science which deals with the ways to learn the information from the given content is Machine Learning. The ways to project the diabetes in the starting stage in order to control it by taking the several results obtained by the machine learning techniques and comparing them with each other to get the most accurate decision are such as K nearest neighbor, random forest, decision tree, logistical regression are used. By using these kind of algorithms we can calculate the accuracy of the algorithms

Keywords : Symptoms, Types, Random forest ,Decision tree, Logistic regression, KNN.

Diabetes is a chronic disease that occurs when the blood sugar levels of a human are high. When we ate, body turns the food into sugar(glucose). Big Data Analytics plays important role in the care industries. It can help in identifying the right treatment for people with diabetes. Care industries have massive volume of databases. Kidneys are mainly damaged by the diseases called diabetes damage, blindness, heart failure. Normally pancreas is supposed to release insulin. The future scientific field in the course of data science which deals with the ways to learn the information from the given content is Machine Learning. The ways to project the diabetes in the starting stage in order to control it by taking the several results obtained by the machine learning techniques and comparing them with each other to get the most accurate decision are such as K nearest neighbor, random forest, decision tree, logistical regression are used. By using these kind of algorithms we can calculate the accuracy of the algorithms

Keywords : Symptoms, Types, Random forest ,Decision tree, Logistic regression, KNN.

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