| dc.contributor.author | Sweetnam, Connor | |
| dc.contributor.author | Mocellin, Simone | |
| dc.contributor.author | Krauthammer, Michael | |
| dc.contributor.author | Baertsch, Robert | |
| dc.contributor.author | Shrager, Jeff | |
| dc.contributor.author | Knopf, Nathaniel D. | |
| dc.date.accessioned | 2018-10-01T17:40:17Z | |
| dc.date.available | 2018-10-01T17:40:17Z | |
| dc.date.issued | 2018-09 | |
| dc.date.submitted | 2017-10 | |
| dc.identifier.issn | 1471-2105 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/118317 | |
| dc.description.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 | en_US |
| dc.description.sponsorship | Cancer Commons | en_US |
| dc.description.sponsorship | Deloitte Touche Tohmatsu (Firm) | en_US |
| dc.publisher | BioMed Central | en_US |
| dc.relation.isversionof | https://doi.org/10.1186/s12859-018-2374-0 | en_US |
| dc.rights | Creative Commons Attribution | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | BioMed Central | en_US |
| dc.title | Prototyping a precision oncology 3.0 rapid learning platform | en_US |
| dc.type | Article | en_US |
| dc.identifier.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 | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.contributor.mitauthor | Knopf, Nathaniel D. | |
| dc.relation.journal | BMC Bioinformatics | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2018-09-30T03:52:54Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The Author(s). | |
| dspace.orderedauthors | Sweetnam, Connor; Mocellin, Simone; Krauthammer, Michael; Knopf, Nathaniel; Baertsch, Robert; Shrager, Jeff | en_US |
| dspace.embargo.terms | N | en_US |
| mit.license | PUBLISHER_CC | en_US |
