CEDARS: Simple and Efficient Pipeline for Electronic Health Record Annotation

Streamlined annotation pipeline for collection and aggregation of time-to-event data in retrospective clinical studies. 'CEDARS' aims to systematize and accelerate the review of electronic health record (EHR) corpora. It accomplishes those goals by deploying natural language processing as a tool to assist detection and characterization of clinical events by human abstractors. The online user manual presents the necessary steps to install 'CEDARS', process EHR corpora and obtain clinical event dates: <https://cedars.io>.

Version: 1.90
Depends: R (≥ 3.5.0)
Imports: fastmatch, jsonlite, mongolite, parallel, readr, shiny, udpipe, utils
Published: 2021-02-07
Author: Simon Mantha ORCID iD [aut, cre]
Maintainer: Simon Mantha <smantha at cedars.io>
BugReports: https://github.com/simon-hans/CEDARS/issues
License: GPL-3
URL: https://cedars.io (main) https://github.com/simon-hans/CEDARS (devel)
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: CEDARS results

Downloads:

Reference manual: CEDARS.pdf
Package source: CEDARS_1.90.tar.gz
Windows binaries: r-devel: CEDARS_1.90.zip, r-release: CEDARS_1.90.zip, r-oldrel: CEDARS_1.90.zip
macOS binaries: r-release (arm64): CEDARS_1.90.tgz, r-release (x86_64): CEDARS_1.90.tgz, r-oldrel: CEDARS_1.90.tgz

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