Year: 2025
Type: article
Abstract: Diabetes is a global health situation that can impact a patient's whole life. Diabetes affects people of every age group. Developing technology offers a novel technique to predict diabetes and improve efficiency. Researchers mostly take the Pima Indian dataset to predict diabetes. In this study, the authors construct a structure, which can accurately evaluate the chance of diabetes in patients. This research presents a framework for accurately estimating the chance of diabetes in patients. The authors propose using Machine Learning techniques like Decision Trees, SVM, and Naive Bayes to diagnose diabetes in its early stages. The Pima Indian Diabetes test from the UCI library is utilized to predict diabetes, saving time and ensuring accuracy. Key Words: Machine Learning, Decision Tree, Naïve Bayes, Diabetes, Precision, Classification, SVM.
DOI: 10.55041/ijsrem51179
Authors: Priyanka Sopan Mogal, Prof. K D kharat
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4412047757