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Date of Award
12-2022
Document Type
Restricted Project: Campus only access
Degree Name
Master of Science in Computer Science
Department
School of Computer Science and Engineering
First Reader/Committee Chair
Jennifer Jin
Abstract
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.
Recommended Citation
Kajuluri, Raja, "HIGH-RISK PREDICTION FOR COVID-19 PATIENTS USING MACHINE LEARNING" (2022). Electronic Theses, Projects, and Dissertations. 1579.
https://scholarworks.lib.csusb.edu/etd/1579