Electrical & Computer Engineering, Department of
First Advisor
Qing Hui
Second Advisor
Hamid Vakilzadian
Third Advisor
Ashok Samal
Date of this Version
Summer 5-16-2018
Citation
Zhou, Y 2018, "Design of A Distributed Real-time E-Health Cyber Ecosystem with Collective Actions: Diagnosis, Dynamic Queueing, and Decision Making", Master of Science, University of Nebraska-Lincoln, Lincoln, NE, USA
Abstract
In this thesis, we develop a framework for E-health Cyber Ecosystems, and look into different involved actors. The three interested parties in the ecosystem including patients, doctors, and healthcare providers are discussed in 3 different phases. In Phase 1, machine-learning based modeling and simulation analysis is performed to remotely predict a patient's risk level of having heart diseases in real time. In Phase 2, an online dynamic queueing model is devised to pair doctors with patients having high risk levels (diagnosed in Phase 1) to confirm the risk, and provide help. In Phase 3, a decision making paradigm is proposed to help regional healthcare providers to logistically rearrange regional medical resources. Therefore, this thesis provides an end-to-end solution on: Health Risk Identification, Risk Level Confirmation, and Regional Health Alert Level Decision Support.
Adviser: Qing Hui
Included in
Biomedical Devices and Instrumentation Commons, Cardiovascular Diseases Commons, Computational Engineering Commons, Computer Engineering Commons, Controls and Control Theory Commons, Diagnosis Commons, Industrial Engineering Commons, Other Electrical and Computer Engineering Commons, Risk Analysis Commons
Comments
A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Master of Science, Major: Electrical Engineering, Under the Supervision of Professor Qing Hui. Lincoln, Nebraska: May, 2018
Copyright 2018 Yanlin Zhou