In OHDSI/Hades: Health Analytics Data-to-Evidence Suite
Below are the packages included in HADES. For each package a link is provided with more information, including instructions on how to install and use the package.
Population-level estimation
CohortMethod
New-user cohort studies using large-scale regression for propensity and outcome models.Learn more... SelfControlledCaseSeries
Self-Controlled Case Series analysis using few or many predictors, includes splines for age and seasonality.Learn more... SelfControlledCohort
A self-controlled cohort design, where time preceding exposure is used as control.Learn more... EvidenceSynthesis
Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study.Learn more...
Patient-level prediction
PatientLevelPrediction
Build and evaluate predictive models for user-specified outcomes, using a wide array of machine learning algorithms.Learn more... DeepPatientLevelPrediction
Performing patient level prediction using deep learningLearn more... EnsemblePatientLevelPrediction
Building and validating ensemble patient-level predictive models.Learn more...
Characterization
Characterization
Various types of characterizations of a target and outcome cohort.Learn more... CohortIncidence
Compute incidence rates and proportionsLearn more... TreatmentPatterns
Analyze treatment patterns of a study population of interestÊLearn more...
Cohort construction and evaluation
Capr
Develop and manipulate complex cohort definitions in RLearn more... CirceR
An R wrapper for Circe, a library for creating cohort definitions, expressing them as JSON, SQL, or Markdown.Learn more... CohortGenerator
Instantiating cohorts in a database based on a set of cohort definitions.Learn more... PhenotypeLibrary
The OHDSI Phenotype Library: a collection of community-maintained pre-definined cohorts.Learn more... CohortDiagnostics
Generate a wide set of diagnostics to evaluate cohort definitions against databases in the CDM.Learn more... PheValuator
Semi-automated evaluation of cohorts, producing metrics suchs as sensitivity, specificity, and positive and negative preditive value.Learn more... CohortExplorer
Visually explore all individual-level data of patients in a cohortLearn more... Keeper
Knowledge-Enhanced Electronic Profile ReviewLearn more...
Evidence Quality
Achilles
Generate descriptive statistics on an entire OMOP CDM databaseLearn more... DataQualityDashboard
Expose and evaluate observational data quality.Learn more... EmpiricalCalibration
Use negative control exposure-outcome pairs to profile and calibrate a particular analysis design.Learn more... MethodEvaluation
Use real data and established reference sets as well as simulations injected in real data to evaluate the performance of methods.Learn more...
Supporting packages
Andromeda
Storing very large data objects on a local drive, while still making it possible to manipulate the data in an efficient manner.Learn more... BigKnn
A large scale k-nearest neighbor classifier using the Lucene search engine.Learn more... BrokenAdaptiveRidge
Broken Adaptive Ridge Regression with Cyclops.Learn more... Cyclops
Highly efficient implementation of regularized logistic, Poisson and Cox regression.Learn more... DatabaseConnector
Connect directly to a wide range of database platforms, including SQL Server, Oracle, and PostgreSQL.Learn more... Eunomia
A standard CDM dataset for testing and demonstration purposes that runs on an embedded SQLite database.Learn more... FeatureExtraction
Automatically extract large sets of features for user-specified cohorts using data in the CDM.Learn more... Hydra
Hydrating package skeletons into executable R study packages based on specifications in JSON format.Learn more... IterativeHardThresholding
Performing L0-based regressions using CyclopsLearn more... OhdsiSharing
Securely sharing (large) files between OHDSI collaborators.Learn more... OhdsiShinyModules
Contains shiny modules that can be used within shiny result interfacesLearn more... ParallelLogger
Support for parallel computation with logging to console, disk, or e-mail.Learn more... ResultModelManager
A lightweight utility for data migrations allowing old results to work with new shiny apps and data visualisations.Learn more... ROhdsiWebApi
Interact with OHDSI WebAPI web services.Learn more... ShinyAppBuilder
Interactively view analysis results across different types of analyses.Learn more... OhdsiShinyAppBuilder
Interactively view analysis results across different types of analyses.Learn more... Strategus
Coordinating and executing analytics using HADES packagesLearn more... SqlRender
Generate SQL on the fly for the various SQL dialects.Learn more... OhdsiReportGenerator
Extract data from the OHDSI results structure and generate plots, presentations and reportsLearn more...
OHDSI/Hades documentation built on April 3, 2025, 3:06 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Below are the packages included in HADES. For each package a link is provided with more information, including instructions on how to install and use the package.
Population-level estimation
CohortMethod
New-user cohort studies using large-scale regression for propensity and outcome models.Learn more...SelfControlledCaseSeries
Self-Controlled Case Series analysis using few or many predictors, includes splines for age and seasonality.Learn more...SelfControlledCohort
A self-controlled cohort design, where time preceding exposure is used as control.Learn more...EvidenceSynthesis
Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study.Learn more...
Patient-level prediction
PatientLevelPrediction
Build and evaluate predictive models for user-specified outcomes, using a wide array of machine learning algorithms.Learn more...DeepPatientLevelPrediction
Performing patient level prediction using deep learningLearn more...EnsemblePatientLevelPrediction
Building and validating ensemble patient-level predictive models.Learn more...
Characterization
Characterization
Various types of characterizations of a target and outcome cohort.Learn more...CohortIncidence
Compute incidence rates and proportionsLearn more...TreatmentPatterns
Analyze treatment patterns of a study population of interestÊLearn more...
Cohort construction and evaluation
Capr
Develop and manipulate complex cohort definitions in RLearn more...CirceR
An R wrapper for Circe, a library for creating cohort definitions, expressing them as JSON, SQL, or Markdown.Learn more...CohortGenerator
Instantiating cohorts in a database based on a set of cohort definitions.Learn more...PhenotypeLibrary
The OHDSI Phenotype Library: a collection of community-maintained pre-definined cohorts.Learn more...CohortDiagnostics
Generate a wide set of diagnostics to evaluate cohort definitions against databases in the CDM.Learn more...PheValuator
Semi-automated evaluation of cohorts, producing metrics suchs as sensitivity, specificity, and positive and negative preditive value.Learn more...CohortExplorer
Visually explore all individual-level data of patients in a cohortLearn more...Keeper
Knowledge-Enhanced Electronic Profile ReviewLearn more...
Evidence Quality
Achilles
Generate descriptive statistics on an entire OMOP CDM databaseLearn more...DataQualityDashboard
Expose and evaluate observational data quality.Learn more...EmpiricalCalibration
Use negative control exposure-outcome pairs to profile and calibrate a particular analysis design.Learn more...MethodEvaluation
Use real data and established reference sets as well as simulations injected in real data to evaluate the performance of methods.Learn more...
Supporting packages
Andromeda
Storing very large data objects on a local drive, while still making it possible to manipulate the data in an efficient manner.Learn more...BigKnn
A large scale k-nearest neighbor classifier using the Lucene search engine.Learn more...BrokenAdaptiveRidge
Broken Adaptive Ridge Regression with Cyclops.Learn more...Cyclops
Highly efficient implementation of regularized logistic, Poisson and Cox regression.Learn more...DatabaseConnector
Connect directly to a wide range of database platforms, including SQL Server, Oracle, and PostgreSQL.Learn more...Eunomia
A standard CDM dataset for testing and demonstration purposes that runs on an embedded SQLite database.Learn more...FeatureExtraction
Automatically extract large sets of features for user-specified cohorts using data in the CDM.Learn more...Hydra
Hydrating package skeletons into executable R study packages based on specifications in JSON format.Learn more...IterativeHardThresholding
Performing L0-based regressions using CyclopsLearn more...OhdsiSharing
Securely sharing (large) files between OHDSI collaborators.Learn more...OhdsiShinyModules
Contains shiny modules that can be used within shiny result interfacesLearn more...ParallelLogger
Support for parallel computation with logging to console, disk, or e-mail.Learn more...ResultModelManager
A lightweight utility for data migrations allowing old results to work with new shiny apps and data visualisations.Learn more...ROhdsiWebApi
Interact with OHDSI WebAPI web services.Learn more...ShinyAppBuilder
Interactively view analysis results across different types of analyses.Learn more...OhdsiShinyAppBuilder
Interactively view analysis results across different types of analyses.Learn more...Strategus
Coordinating and executing analytics using HADES packagesLearn more...SqlRender
Generate SQL on the fly for the various SQL dialects.Learn more...OhdsiReportGenerator
Extract data from the OHDSI results structure and generate plots, presentations and reportsLearn more...
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.