Diabetes Prediction Using Machine Learning KNN -Algorithm Technique

Diabetes Prediction Using Machine Learning KNN -Algorithm Technique

Nikhil Reddy Nookala (Author) CSE Student

Hyderabad, India

nookalanikhil007@gmail.com

Abstract:- Diabetes is a chronic condition characterized by an excess of glucose in the human body. If diabetes is not treated, it can lead to serious health problems such as renal failure, heart attacks, high blood pressure, eye damage, weight loss, frequent urination, and so on. Insulin, which is generated by the pancreas, is found in the human body. This insulin aids in the entry of glucose into blood cells, where it is converted into energy for the body. Diabetes is classified into two types: Kind 1 and Type 2. Another type is gestational diabetes, which occurs during pregnancy. This can be managed in the early phases of an attack. According to the International Diabetes Federation (IDF), 382 million people have diabetes, with the number expected to treble in the next 20 years to 592 million. To achieve this aim, we may use several machine learning techniques such as Random Forest (RF), K-nearest neighbors (KNN), Decision Trees (DT), and others in this research to predict diabetes in individuals or patients with high accuracy. In this study, however, we are predicting diabetes with the KNN classifier model. As we can see these days, machine learning is a developing technology that is a blessing to many issue solutions.