  Each year, over 2.5 million people, most of them in developed countries, die
from pneumonia [1]. Since many studies have proved pneumonia is successfully
treatable when timely and correctly diagnosed, many of diagnosis aids have been
developed, with AI-based methods achieving high accuracies [2]. However,
currently, the usage of AI in pneumonia detection is limited, in particular,
due to challenges in generalizing a locally achieved result. In this report, we
propose a roadmap for creating and integrating a system that attempts to solve
this challenge. We also address various technical, legal, ethical, and
logistical issues, with a blueprint of possible solutions.
