Prototyping a precision oncology 3.0 rapid learning platform

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

doi:10.1186/s12859-018-2374-0

Prototyping a precision oncology 3.0 rapid learning platform

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

Istituto Oncologico Veneto

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	341
Journal	BMC Bioinformatics
Volume	19
Issue number	1
DOIs	https://doi.org/10.1186/s12859-018-2374-0
Publication status	Published - Sep 26 2018

Keywords

Algorithms
Education, Medical
Humans
Medical Oncology
Precision Medicine
Publications
Software

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AU - Mocellin, Simone

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AU - Shrager, Jeff

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KW - Publications

KW - Software

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