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Cost-Effectiveness Analysis of Adaptive Monitoring Strategies for Depression Treatment
Depression is a significant challenge for the American medical care system and affects as high as 10% of the adult population in the U.S. There are many challenges in treating depression. People are reluctant to reveal their symptoms and seek care because many see mental health problem as a personal weakness. Meanwhile, a ...
Modeling Depression Progression Dynamics from Electronic Health Record
To assess and monitor the progression dynamics of patients' depression severity conditions, Markov models are refined from other disease progression modeling methodologies to identify the characteristics and evolvement of disease severity state transitions among a cohort of patients. Explored in this thesis is an integrated ...
Optimization and Machine Learning Frameworks for Complex Network Analysis
Networks are all around us, and they may be connections of tangible objects in the Euclidean space such as electric power grids, the Internet, highways systems, etc. Among the wide range of areas in the network analysis, finding critical component in the large scale complex networks is one of the most challenging but fascinating ...
Discrete-event Simulation and Optimization to Improve the Performance of a Healthcare System
Healthcare systems have attracted the attention of management and analysis due to their high percentage of the gross domestic product (GDP) and increasing rate of growth of expenditures. Within the various types of healthcare problems, this dissertation focuses on resource allocation decisions because they can significantly ...
Approximating Large-Scale Binary Integer Programs by Discrete Optimal Control
Optimal control theory has been introduced as a powerful tool for approximately solving binary integer programming problems. In previous studies, an approach using continuous optimal control theory was developed, where the original binary integer problem was transformed into a continuous linear quadratic problem. However, the ...
Explicitly Controlling Geometric Characteristics of Corridors in Spatial Optimization
Spatially-explicit mixed-integer programming models (MIPs) allow decision makers to explore a variety of complex scenarios and determine optimal sets of actions across a landscape. In reserve selection problems, the landscape is partitioned into units, and the decision maker must select which units to include in a wildlife ...
Reducing Disruptive Effects of Patient No-shows: A Scheduling Approach
(2013-11-14)
Appointment scheduling systems have been studied for nearly 60 years. From a decision making point of view, related problems can be classified into two categories: static and dynamic. In a static scheduling problem, all decisions are made before a clinic session starts; in a dynamic scheduling problem, the schedule of future ...
Scheduling Mass Customized Large Product Assembly Line Considering Learning Effect and Shifting Bottleneck
(2014-04-30)
The large product assembly industry is a complex and heavily manually based assembly manufacturing process. Examples are commercial airplanes, ships, and wind turbines. These manufacturing enterprises are increasingly striving to satisfy the individual needs of customers by providing customized products. Under this circumstance, ...
Improving Efficiency in Allocating Pediatric Ambulatory Care Clinics
Low utilized resources is a common problem in the health care sector. As health care costs and the need for more efficient operations increases, managers are looking for new methods to increase the utilization of their resources. At Seattle Children's Hospital in Seattle, managers of the outpatient pediatric ambulatory care ...