Andrew J. Schaefer

TL;DR: Excess cases of pediatric and maternal disease, death, and costs attributable to suboptimal breastfeeding rates in the United States and policies to increase optimal breastfeeding could result in substantial public health gains.

TL;DR: This tutorial provides a tutorial on the construction and evaluation of Markov decision processes (MDPs), which are powerful analytical tools used for sequential decision making under uncertainty that have been widely used in many industrial and manufacturing applications but are underutilized in medical decision making (MDM).

TL;DR: This work considers the problem of optimally timing a living-donor liver transplant to maximize the patient's total reward, such as quality-adjusted life expectancy, and formulate a Markov decision process (MDP) model in which the state of the process is described by patient health.

TL;DR: A novel two-stage stochastic mixed-integer programming model is presented to minimize total expected operating cost given that scheduling decisions are made before the resolution of uncertainty in surgery durations.

TL;DR: This work provides a lower bound on the cost of an optimal crew schedule in operations, and it is demonstrated that some of the crew schedules found using the method perform very well relative to this lower bound.