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CohortDiagnostics v3.1.1 has been released.
This release contains a bug fixes for the shiny application as well as support for custom features in the FeatureExtraction characterization.
The CohortExplorer shiny app has also been removed as it’s now part of a dedicated new package.
PheValuator 2.1.13 has been released. This is the first release of this package that has all the requirements for HADES.
PheValuator is an R package built using many other HADES packages including PatientLevelPrediction. The package is used to determine the performance characteristics, i.e., sensitivity, specificity, and positive and negative predictive value.
PheValuator follows a multi-step process to determine the performance characteristics of phenotype algorithms. In the first step, phenotype algorithms must be developed manually to identify subjects very likely with and those very likely without the health condition of interest. Those algorithms are used to generate highly accurate labels for subjects in the next step of the process, where a diagnostic predictive model is trained for the health condition. The diagnostic predictive model is next applied to a large, random sample of subjects from the database to determine the probability of each of these subjects of having the health condition. We refer to this set of subjects as the “probabilistic gold standard” dataset. In the final step, we evaluate potential research phenotype algorithms against the probabilistic gold standard and, based on the estimated probabilities, determine the performance characteristics of the tested algorithm. PheValuator has been used on many different type of phenotype algorithms, both those for acute health conditions as well as chronic health conditions.
ParallelLogger 3.1.0 has been released. This includes some quality-of-life improvements, and a minor bug fix.
Some what improvements? 
OhdsiShinyModules 1.0.1 has been released. This R package contains shiny modules that can be reused inside other shiny apps presenting OHDSI results. The package currently contains modules for:
Please see here if you are interested in adding new shiny modules.
DeepPatientLevelPrediction 1.0.2 has been released. This includes a small fix to make sure the dependencies install correctly when running tests from outside the package.
SelfControlledCaseSeries 4.0.0 has been released. This release includes major changes to the way multi-analyses studies are defined and executed. The main reason is to support the new HADES ‘JSON specifications in - shareable CSV files out’ paradigm. Importantly, the package can now produce CSV files according to the data model specified here. A shiny app for viewing these results is being developed.
CohortDiagnostics v3.1.2 has been released.
This is a hotfix that removes taking a package dependency snapshot that was breaking with newer versions of R on some systems and breaking automated builds.
SelfControlledCaseSeries 4.1.0 has been released. Most important change is undoing the change from string to Date for the studyStartDate and studyEndDate arguments (in V4.0.0), since Dates are annoying to deal with in JSON.
EvidenceSynthesis 0.4.0 has just been released. This provides wider support for the adaptive grid likelihood approximation (as well as a neat visualization of likelihood curves in the forest plot).
SqlRender 1.11.1 has been released. This includes some minor changes in preparation for DatabaseConnector 6.0.0.
Characterization 0.0.5 has been released. This is a new analysis package for executing various characterization studies such as time-to-event, dechallenge/rechallenge and descriptive studies of target populations experiencing an outcome within a user defined time-at-risk and not experiencing an outcome within a time-at-risk.
SqlRender 1.12.0 has been released, including some final changes required for the upcoming DatabaseConnector 6.0.0 (which will be released early next week).
CirceR 1.3.0 has been released, introducing a new function buildConceptSetQuery() to generate queries from concept set expression JSON.
DatabaseConnector 6.0.0 has been released. There are many changes, but these are the most important:
dbplyr, which some users seem to prefer over translating OhdsiSql. An important limitation is that field names must be case insensitive (lowercase in R), because by default most database platforms are case-insensitive. DatabaseConnector also includes various date functions for dbplyr, such as dateAdd() and dateDiff() (dbplyr itself doesn’t support date operations).computeDataHash() function. This computes a hash based on the table structures and row counts in a database schema, so in theory will be stable as long as the data doesn’t change. This should be useful in distributed research network, where for example this function can be used to check whether the data has changed since the last DataQualityDashboard results.options(LOG_DATABASECONNECTOR_SQL = TRUE) option and extractQueryTimes() function, which together can be used to monitor query performance via the ParallelLogger log.OhdsiShinyModules v1.0.2 has been released. There are a four changes:
ShinyAppBuilder v1.1.1 has been released. This is a new HADES package that lets you build shiny apps that combine multiple modules from OhdsiShinyModules or custom modules that match the module standards.
There is code for creating shiny apps for shiny servers or opening the shiny app locally.
ResultModelManager v0.3.0 has been released.
This release added functionality for uploading results data sets to servers in a robust manner, conforming to a results schema data.frame definition.
For a usage guide on this new functionality, please see this article.
CohortExplorer v0.0.11 has been updated. Just routine clean up so that github actions doesn’t complain And ofcourse 100% test coverage
ROhdsiWebApi 1.3.2 has been released. This contains some minor changes to allow the released version to pass R Check again.