Bayesian Networks for Health Economics and Public Policy Research
Wednesday, June 6, 2018, 2:00 p.m. – 5:00 p.m.
MaRS Centre, South Tower, Room CR3
101 College Street, Toronto, ON M5G 1L7
In this seminar, we will illustrate four prototypical examples of applied research with Bayesian networks related to health economics and public policy.
- Diagnostic decision support: using Bayesian networks for cost-effective evidence-seeking.
- The value of a priori information in field triage: defining asymmetrical, dynamic 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.
- Causal inference from observational healthcare data: using 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.
A detailed abstract is forthcoming.
Who should attend?
Biostatisticians, clinical scientists, data scientists, decision scientists, demographers, ecologists, econometricians, economists, epidemiologists, knowledge managers, management scientists, market researchers, marketing scientists, operations research analysts, policy analysts, predictive modelers, research investigators, risk managers, social scientists, statisticians, plus students and teachers of related fields.
Please note that this seminar is geared towards applied researchers, NOT software developers or computer scientists. Questions related to algorithms, programming, scalability, architecture, infrastructure, etc., will be out of scope at this event.