| Summary: | Background: We describe a prototype implementation of a platform that could underlie a Precision Oncology Rapid Learning system.
Results: We describe the prototype platform, and examine some important issues and details. In the Appendix we provide a complete walk-through of the prototype platform.
Conclusions: The design choices made in this implementation rest upon ten constitutive hypotheses, which, taken together, define a particular view of how a rapid learning medical platform might be defined, organized, and implemented. Keywords: Natural language processing, Precision oncology, Controlled natural language, Nanopublication, Treatment reasoning, Rapid learning, Tumor boards, Targeted therapies
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