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Date of Award


Document Type

Restricted Project: Campus only access

Degree Name

Master of Science in Computer Science


School of Computer Science and Engineering

First Reader/Committee Chair

Jennifer Jin


This Machine Learning algorithm offers a prediction methodology for potentially detecting severely affected COVID-19 patients based on blood sample parameters that are readily available. The development of effective and efficient treatment regimens for critical patients as well as routine patient monitoring for low-risk may be aided by these findings, which would also help to ease the patient flow in hospitals. They can be used to analyze how often hospital beds are used. Classifying COVID-19-affected patients as critical patients who need hospitalization or low-risk patients who might not need hospitalization is more accurate using the current machine learning-based methodologies.