Diabetes Prediction Using Machine Learning KNN -Algorithm Technique


Authors : Dr. B. Premamayudu; K. Muralikrishna; K. Pramodh

Volume/Issue : Volume 7 - 2022, Issue 5 - May

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

Scribd : https://bit.ly/3NPlZq4

DOI : https://doi.org/10.5281/zenodo.6642320

Diabetes is a chronic disease caused due to high amount of glucose present in the human body. If this diabetes is ignored, this may lead to severe health problems such as kidney failure, heart attacks, blood pressure, eye damage, weight loss, frequent urination, etc. Basically, human body contains Insulin which is produced by pancreas. This insulin helps to enter glucose in to blood cells in order to generate energy to the body. There are types in diabetes Type1 and Type 2 other form is gestational diabetes which is caused during pregnancy. This can be controlled in the earlier stages of the attack. According to International Diabetes Federation (IDF) 382 million people are suffering with diabetes and by next 20years the count will be doubled as 592 million. To accomplish this goal, in this project we can do early prediction of diabetes in humans or patients for good accuracy through applying various machine learning techniques such as Random Forest (RF), K-nearest neighbors (KNN), Decision Trees (DT), etc. However, in this project we are predicting diabetes using KNN classifier model. As we see now a days machine learning is an emerging technology and boon to many problem solutions.

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Paper Submission Last Date
29 - February - 2024

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