Package: CohortContrast 1.0.0
Markus Haug
CohortContrast: Enrichment Analysis of Clinically Relevant Concepts in Common Data Model Cohort Data
Identifies clinically relevant concepts in Observational Medical Outcomes Partnership Common Data Model cohorts using an enrichment-based workflow. Defines target and control cohorts and extracts medical interventions that are over-represented in the target cohort during the observation period. Users can tune filtering and selection thresholds. The workflow includes chi-squared tests for two proportions with Yates continuity correction, logistic tests, and hierarchy and correlation mappings for relevant concepts. The results can be optionally explored using the bundled graphical user interface. For workflow details and examples, see <https://healthinformaticsut.github.io/CohortContrast/>.
Authors:
CohortContrast_1.0.0.tar.gz
CohortContrast_1.0.0.zip(r-4.7)CohortContrast_1.0.0.zip(r-4.6)CohortContrast_1.0.0.zip(r-4.5)
CohortContrast_1.0.0.tgz(r-4.6-any)CohortContrast_1.0.0.tgz(r-4.5-any)
CohortContrast_1.0.0.tar.gz(r-4.7-any)CohortContrast_1.0.0.tar.gz(r-4.6-any)
CohortContrast_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CohortContrast/json (API)
| # Install 'CohortContrast' in R: |
| install.packages('CohortContrast', repos = c('https://healthinformaticsut.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/healthinformaticsut/cohortcontrast/issues
Pkgdown/docs site:https://healthinformaticsut.github.io
Last updated from:bc5d0b2de1. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 202 | ||
| source / vignettes | OK | 266 | ||
| linux-release-x86_64 | NOTE | 142 | ||
| macos-release-arm64 | NOTE | 157 | ||
| macos-oldrel-arm64 | NOTE | 199 | ||
| windows-devel | NOTE | 145 | ||
| windows-release | NOTE | 114 | ||
| windows-oldrel | NOTE | 150 | ||
| wasm-release | OK | 130 |
Exports:automaticCorrelationCombineConceptsautomaticHierarchyCombineConceptscheckDataModecheckPythonDepsCohortContrastcohortFromCohortTablecohortFromCSVcohortFromDataTablecohortFromJSONconfigurePythoncreateControlCohortInversecreateControlCohortMatchinggenerateMappingTablegetPythonInfogetTopSeparatingConceptsinstallPythonDepsinstallPythonDepsOfflineloadCohortContrastStudymatchCohortsByAgenGramClusterSummarizationnGramDiscoveryprecomputeSummaryremoveTemporalBiasresolveCohortTableOverlapsrunCohortContrastViewerstopCohortContrastViewer
Dependencies:askpassbackportsbitbit64blobCDMConnectorcheckmateclicliprclockCodelistGeneratorcodetoolsCohortConstructorcpp11crayoncurldata.tableDBIdbplyrdoParalleldplyrforeachgenericsgluehmshttriteratorsjsonlitelifecyclelubridatemagrittrmimenanoparquetomopgenericsopensslPatientProfilespillarpkgconfigprettyunitsprogresspurrrR6readrrlangsnakecasestringistringrsystibbletidyrtidyselecttimechangetzdbutf8vctrsvroomwithr
Air-gapped Server Setup
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Article Case Study Generation
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Dashboard Composite Plot
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Demographics Tab
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Execution
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Graphical User Interface
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ICD10 Atlas Generation
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Interpreting Results with lc500
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Interpreting Summary Results with lc500s
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Mappings Tab
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Overlap Tab
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Patient vs Summary Mode
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Setup
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Sidepanel Filters and Controls
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Trajectories Tab
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