Predictive Modelling Of Mortality Rates for Diabetes: An Analysis Of Risk Factors

Authors

Presenter(s)

Simin Zhao

Comments

Presentation: 11:20-11:40 p.m., Science Center 119

Files

Description

Diabetes is a chronic disease affecting millions globally and is a leading cause of death. Understanding mortality trends and predicting future mortality rates is crucial for public health planning and intervention strategies. This project analyzes mortality rates for diabetes in the United States from 2015 to 2020 and employs various predictive methods in Statistics and Machine Learning to forecast future mortality rates. Our objective is to identify critical factors that contribute to mortality from diabetes and develop a suitable model for predicting future mortality rates. The outcomes of this study could inform policies and interventions aimed at reducing the burden of diabetes-related mortality.

Publication Date

4-19-2023

Project Designation

Capstone Project

Primary Advisor

Ying-Ju Chen

Primary Advisor's Department

Mathematics

Keywords

Stander Symposium, College of Arts and Sciences

Institutional Learning Goals

Community; Practical Wisdom; Diversity

Recommended Citation

"Predictive Modelling Of Mortality Rates for Diabetes: An Analysis Of Risk Factors" (2023). Stander Symposium Projects. 2959.
https://ecommons.udayton.edu/stander_posters/2959