Prototyping a precision oncology 3.0 rapid learning platform

Author(s)
Sweetnam, Connor; Mocellin, Simone; Krauthammer, Michael; Baertsch, Robert; Shrager, Jeff; ... Show more
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Abstract
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
Date issued
2018-09
URI
http://hdl.handle.net/1721.1/118317
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
BMC Bioinformatics
Publisher
BioMed Central
Citation
Sweetnam, Connor, et al. “Prototyping a Precision Oncology 3.0 Rapid Learning Platform.” BMC Bioinformatics, vol. 19, no. 1, Dec. 2018. © 2018 The Authors
Version: Final published version
ISSN
1471-2105
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