Prototyping a precision oncology 3.0 rapid learning platform

Connor Sweetnam, Simone Mocellin, Michael Krauthammer, Nathaniel Knopf, Robert Baertsch, Jeff Shrager

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)341
JournalBMC Bioinformatics
Issue number1
Publication statusPublished - Sep 26 2018


  • Algorithms
  • Education, Medical
  • Humans
  • Medical Oncology
  • Precision Medicine
  • Publications
  • Software


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