GC-54 COVID-19 Mortality Prediction using Machine Learning Techniques
Description
In late 2019, SARS-CoV2 also known as COVID-19 was first identified in the city of Wuhan, China. This virus can infect a person and without showing any signs of sickness, can spread of COVID-19 unknowingly. The World Health Organization declared it a global pandemic in March 2020 because of its far-reaching effects in every part of the world. Scientists have been working to leverage technology to prevent spread, detection and vaccine development. With machine learning, models can predict which patient will most likely have a higher mortality rate. Using WEKA, a machine learning tool and a data set based on 95,000 Mexican patients with 20 clinical features, our research applies models to determine which has the most accuracy. Advisors(s): Dr. Seyedamin PouriyehTopic(s): Other (explain in the comments section)Machine Learning
GC-54 COVID-19 Mortality Prediction using Machine Learning Techniques
https://ccse.kennesaw.edu/computing-showcase/cday-programs/spring2021program.php
In late 2019, SARS-CoV2 also known as COVID-19 was first identified in the city of Wuhan, China. This virus can infect a person and without showing any signs of sickness, can spread of COVID-19 unknowingly. The World Health Organization declared it a global pandemic in March 2020 because of its far-reaching effects in every part of the world. Scientists have been working to leverage technology to prevent spread, detection and vaccine development. With machine learning, models can predict which patient will most likely have a higher mortality rate. Using WEKA, a machine learning tool and a data set based on 95,000 Mexican patients with 20 clinical features, our research applies models to determine which has the most accuracy. Advisors(s): Dr. Seyedamin PouriyehTopic(s): Other (explain in the comments section)Machine Learning
https://digitalcommons.kennesaw.edu/cday/Fall2021/Graduate_Capstone/4