ABSTRACT
In this position paper, we discuss the potential use of a reinforcement learning (RL)-based human-in-the-loop recommender system to support clinical management of COVID-19. COVID-19 is a disease of extraordinary complexity that even the most experienced clinicians are struggling to understand. There is an urgent need for an evidence-based model for predicting the severity of the COVID-19 disease and its complications that can guide individual clinical management decisions. Such a model will utilize a diverse set of information to determine a patient's disease severity and associated risk of complications. An immediate application would be a clinical protocol tailored for COVID-19 patient care;this is a critical need both today and for future studies of potential treatments. © 2020 Copyright for the individual papers remains with the authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).