학술논문
Comparative Analysis of Machine Learning Models for Diabetes Mellitus Type 2 Prediction
Document Type
Conference
Author
Source
2020 International Conference on Computational Science and Computational Intelligence (CSCI) CSCI Computational Science and Computational Intelligence (CSCI), 2020 International Conference on. :527-533 Dec, 2020
Subject
Language
Abstract
Diabetes is one of the top 10 causes of death worldwide. Health professionals are aiming for machine learning models to support the prognosis of diabetes for better healthcare and to put in place an effective prevention plan. In this paper, we conduct a comparative analysis of the most used machine learning models in the literature to predict the prevalence of diabetes mellitus type 2. We evaluate the models in terms of accuracy, F-measure and execution time with and without feature selection using a real-life diabetes dataset. The detailed analysis is in the paper.