Actionable Bayesian Analysis for Evolving Health Goals

Many people, especially those with chronic health conditions such as iritable bowel syndrome and chronic migraine, track health related variables with the hope of discovering connections between causes and symptoms and enabling more informed choices regarding their health. Gaining actionable insights from this kind of data is known to be difficult because current tools often fail to automatically analyze data in scientifically rigorous, helpful, and actionable ways. Additionally, current tools often fail to account for lapses in tracking, evolving health goals, and the growing burden of tracking more information. This tool uses Bayesian network analysis framework to support individuals in analyzing their personal health data in evolving real life contexts.

Alex Okeson
PhD Student


As AI becomes an increasingly ubiquitous component of end-user systems, questions of effective design of these systems should be …