A Comparative Study of Predictive Modelling of Diabetes Using Machine Learning Algorithms
Abstract: Diabetes is a condition that occurs when your blood sugar (glucose) levels are too high. It occurs when the body cannot make enough insulin or cannot use insulin effectively, which then enters the bloodstream. Insulin is a hormone that helps the body to let glucose enter our cells and use it as fuel. It is secreted by the pancreas. Diabetes occurs when you do not make enough insulin or do not make it at all, or when your body is not responding properly to the effects of insulin. Diabetes affects people of all ages. Most forms of diabetes are long-term (lifelong), and all forms can be controlled with medicines and/or lifestyle changes. Glucose (sugar) comes mainly from carbohydrates in your food and drinks. It is your body's energy source. Your blood carries glucose to all the cells in your body for energy. The main types of diabetes are: type 1 diabetes, type 2 diabetes, and gestational diabetes.[14] It occurs during pregnancy. If left untreated, diabetes can lead to a number of serious health problems, such as heart disease, kidney disease, vision loss, and nerve damage. This study demonstrates how machine learning can be used to predict the likelihood of developing diabetes. Machine learning has a significant impact on the diagnosis and early detection of diabetes. Keywords — Diabetes, Type 1 Diabetes, Type 2 Diabetes, gestational diabetes, Insulin, Glucose, Machine Learning.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-14
- DOI
- https://doi.org/10.5281/zenodo.16871142
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00