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PheCAP

High-Throughput Phenotyping with EHR using a Common Automated Pipeline

v1.2.1 · Sep 17, 2020 · GPL-3

Description

Implement surrogate-assisted feature extraction (SAFE) and common machine learning approaches to train and validate phenotyping models. Background and details about the methods can be found at Zhang et al. (2019) <doi:10.1038/s41596-019-0227-6>, Yu et al. (2017) <doi:10.1093/jamia/ocw135>, and Liao et al. (2015) <doi:10.1136/bmj.h1885>.

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r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
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r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
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r-release-windows-x86_64 OK
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OK r-devel-linux-x86_64-debian-gcc

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OK r-oldrel-macos-arm64

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NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  5.4Mb
  sub-directories of 1Mb or more:
    data   3.4Mb
    doc    1.9Mb
OK r-oldrel-windows-x86_64

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OK r-patched-linux-x86_64

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OK r-release-linux-x86_64

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OK r-release-macos-arm64

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OK r-release-windows-x86_64

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Check History

NOTE 13 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  5.4Mb
  sub-directories of 1Mb or more:
    data   3.4Mb
    doc    1.9Mb

Dependency Network

Dependencies Reverse dependencies glmnet RMySQL PheCAP

Version History

new 1.2.1 Mar 9, 2026