Understanding the progression of Alzheimer's

Bayesian Data Analysis
Bayesian Data Analysis
Public group
Location image of event venue


During this meetup, Arya Pourzanjani, a PhD candidate at the University of Santa Barbara, is going to talk about how he applies Bayesian Inference to Alzheimer's Disease modeling to understand all the possible progression paths a patient can take and the causal effect certain Alzheimer's drugs have on the ultimate progression of the disease.

The progression of Alzheimer’s Disease is characterized by the gradual deterioration of biomarkers and eventual loss of basic memory and decision-making functions. Using these biomarker values and other tests to estimate how far an individual has progressed in the disease is valuable in diagnosis as well as in assessing the efficacy of interventions.

To demonstrate the methods, we will be fitting Stan models to an open source Alzheimer's dataset containing longitudinal biomarkers.

If you want to learn a bit more about the topic prior to the meetup, Arya wrote up a more detailed summary on our blog.


Pizza will arrive at 6:30 and we will start the talk at 7.