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In order to bridge the gap between Deep Learning researchers and medicalprofessionals we develop a very accessible free prototype system which can beused by medical professionals to understand the reality of Deep Learning toolsfor chest X-ray diagnostics. The system is designed to be a second opinionwhere a user can process an image to confirm or aid in their diagnosis. Codeand network weights are delivered via a URL to a web browser (including cellphones) but the patient data remains on the users machine and all processingoccurs 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

Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System