Abstract:

Abstract: In health care, many of the decision made are of a sequential nature. Just think of a doctor continuously modifying the ventilator of an intubated ICU patient or changing the dosage of fluids administered depending on how the patient is doing. Such decision can be supported by AI driven models. Reinforcement Learning (RL) is a very natural fit, however comes with some characteristics that do not fit the medical domain well. In this talk, I will focus on three algorithmic innovations we have made to improve the applicability of RL in the health domain: (1) sample efficient RL; (2) safe RL with domain knowledge, and (3) explainable RL. I will explain the algorithmic improvements, and also show how we have applied these in the health domain. 

General information:

This seminar will be organised in a hybrid setup. If you are interested in joining this seminar, please send an email to the secretariat of Amsterdam Business School at secbs-abs@uva.nl.