Bayesian Networks for Health Economics and Public Policy Research
Seminar on June 6, 2018, in Toronto.
In this seminar, we will illustrate five prototypical examples of applied research with Bayesian networks and BayesiaLab related to health economics and public policy:
- Diagnostic decision support: using Bayesian networks for cost-effective evidence-seeking in diagnosing coronary heart disease.
- Quantifying the value of information in field triage for defining adaptive trauma activation thresholds for the optimal utilization of hospital resources.
- Developing universal policies under extreme uncertainty, e.g., in the absence of epidemiological data: "test & treat" vs. presumptive malaria treatment in sub-Saharan Africa.
- The Chicago Condom Campaign: Simpson's paradox rears its ugly head.
- Causal inference from observational healthcare data: using machine learning and the Disjunctive Cause Criterion to reduce—not eliminate—the need for causal assumptions from domain experts.
Each case study will include a theoretical presentation and a practical demonstration using the BayesiaLab software platform.
- Presentation Slides (PDF, 58.4 MB)
- Example 1: Diagnostic Decision Support
- Example 2: Trauma Activation Policy
- Example 3: Optimizing Health Policies Under Uncertainty
- BayesiaLab Network File (XBL, 2 KB)
- Example 4: Chicago Condom Campaign
- Example 5:
Upcoming Seminars, Webinars, and Conferences
|BayesiaLab Seminar at the DFW Data Science Meetup in Plano, Texas||January 7, 2019||6:30–8:30 p.m. (CST, UTC-6)||Bayesian Networks—Artificial Intelligence for Research, Analytics, and Reasoning|
|Live Webinar||January 17, 2018||10:00–11:00 a.m. (CST, UTC-6)||Introducing the New
|Please check out our archive of recordings of previous events.|