  In order to bridge the gap between Deep Learning researchers and medical
professionals we develop a very accessible free prototype system which can be
used by medical professionals to understand the reality of Deep Learning tools
for chest X-ray diagnostics. The system is designed to be a second opinion
where a user can process an image to confirm or aid in their diagnosis. Code
and network weights are delivered via a URL to a web browser (including cell
phones) but the patient data remains on the users machine and all processing
occurs locally. This paper discusses the three main components in detail:
out-of-distribution detection, disease prediction, and prediction explanation.
The system open source and freely available here: https://mlmed.org/tools/xray
