MORE | Spring 2018
Stochastic Modeling and Optimization to Improve Identification and Treatment of Alzheimer’s Disease
Alzheimer’s Disease (AD) is the 6th leading cause of death in the United States and affects more than 5 million people. AD can be detected at an early stage through biomarker tests including p-Tau, FDG-PET, and hippocampal. This research focuses on the formulation of a Markov Chain (MC) model to predict the AD evolution due to biomarker tests and related results from sequential patient visits to the doctor. Subsequently, a Markov Decision Process (MDP) model provides a guide to doctors to efficiently administer tests and analyze results quickly to understand the AD progression.
Hometown: Chandler, Arizona
Graduation date: Spring 2018