Man pages for OHDSI/PatientLevelPrediction
Developing patient level prediction using data in the OMOP Common Data Model

accuracyCalculate the accuracy
addDiagnosePlpToDatabaseInsert a diagnostic result into a PLP result schema database
addMultipleDiagnosePlpToDatabaseInsert mutliple diagnosePlp results saved to a directory into...
addMultipleRunPlpToDatabasePopulate the PatientLevelPrediction results tables
addRunPlpToDatabaseFunction to add the run plp (development or validation) to...
averagePrecisionCalculate the average precision
brierScorebrierScore
calibrationLinecalibrationLine
computeAucCompute the area under the ROC curve
computeGridPerformanceComputes grid performance with a specified performance...
configurePythonSets up a virtual environment to use for PLP (can be conda or...
covariateSummarycovariateSummary
createCohortCovariateSettingsExtracts covariates based on cohorts
createDatabaseDetailsCreate a setting that holds the details about the cdmDatabase...
createDatabaseListCreate a list with the database details and database meta...
createDatabaseSchemaSettingsCreate the PatientLevelPrediction database result schema...
createDefaultExecuteSettingsCreates default list of settings specifying what parts of...
createDefaultSplitSettingCreate the settings for defining how the plpData are split...
createExecuteSettingsCreates list of settings specifying what parts of runPlp to...
createFeatureEngineeringSettingsCreate the settings for defining any feature engineering that...
createLearningCurvecreateLearningCurve
createLogSettingsCreate the settings for logging the progression of the...
createModelDesignSpecify settings for deceloping a single model
createPlpResultTablesCreate the results tables to store PatientLevelPrediction...
createPreprocessSettingsCreate the settings for preprocessing the trainData.
createRandomForestFeatureSelectionCreate the settings for random foreat based feature selection
createRestrictPlpDataSettingscreateRestrictPlpDataSettings define extra restriction...
createSampleSettingsCreate the settings for defining how the trainData from...
createSplineSettingsCreate the settings for adding a spline for continuous...
createStratifiedImputationSettingsCreate the settings for adding a spline for continuous...
createStudyPopulationCreate a study population
createStudyPopulationSettingscreate the study population settings
createTempModelLocCreate a temporary model location
createUnivariateFeatureSelectionCreate the settings for defining any feature selection that...
createValidationSettingscreateValidationSettings define optional settings for...
diagnoseMultiplePlpRun a list of predictions diagnoses
diagnosePlpdiagnostic - Investigates the prediction problem settings -...
diagnosticOddsRatioCalculate the diagnostic odds ratio
evaluatePlpevaluatePlp
externalValidateDbPlpexternalValidateDbPlp - Validate a model on new databases
extractDatabaseToCsvExports all the results from a database into csv files
f1ScoreCalculate the f1Score
falseDiscoveryRateCalculate the falseDiscoveryRate
falseNegativeRateCalculate the falseNegativeRate
falseOmissionRateCalculate the falseOmissionRate
falsePositiveRateCalculate the falsePositiveRate
fitPlpfitPlp
getCalibrationSummaryGet a sparse summary of the calibration
getCohortCovariateDataExtracts covariates based on cohorts
getDemographicSummaryGet a calibration per age/gender groups
getPlpDataGet the patient level prediction data from the server
getPredictionDistributionCalculates the prediction distribution
getPredictionDistribution_binaryCalculates the prediction distribution
getThresholdSummaryCalculate all measures for sparse ROC
getThresholdSummary_binaryCalculate all measures for sparse ROC when prediction is...
iciCalculate the Integrated Calibration Information from Austin...
insertCsvToDatabaseFunction to insert results into a database from csvs
insertModelDesignInDatabaseInsert a model design into a PLP result schema database
insertResultsToSqliteCreate sqlite database with the results
listAppendjoin two lists
listCartesianCartesian product
loadPlpAnalysesJsonLoad the multiple prediction json settings from a file
loadPlpDataLoad the cohort data from a folder
loadPlpModelloads the plp model
loadPlpResultLoads the evalaution dataframe
loadPlpShareableLoads the plp result saved as json/csv files for transparent...
loadPredictionLoads the prediciton dataframe to csv
MapIdsMap covariate and row Ids so they start from 1
migrateDataModelMigrate Data model
modelBasedConcordanceCalculate the model-based concordance, which is a calculation...
negativeLikelihoodRatioCalculate the negativeLikelihoodRatio
negativePredictiveValueCalculate the negativePredictiveValue
outcomeSurvivalPlotPlot the outcome incidence over time
PatientLevelPredictionPatientLevelPrediction
pfipfi
plotDemographicSummaryPlot the Observed vs. expected incidence, by age and gender
plotF1MeasurePlot the F1 measure efficiency frontier using the sparse...
plotGeneralizabilityPlot the train/test generalizability diagnostic
plotLearningCurveplotLearningCurve
plotPlpPlot all the PatientLevelPrediction plots
plotPrecisionRecallPlot the precision-recall curve using the sparse...
plotPredictedPDFPlot the Predicted probability density function, showing...
plotPredictionDistributionPlot the side-by-side boxplots of prediction distribution, by...
plotPreferencePDFPlot the preference score probability density function,...
plotSmoothCalibrationPlot the smooth calibration as detailed in Calster et al. "A...
plotSparseCalibrationPlot the calibration
plotSparseCalibration2Plot the conventional calibration
plotSparseRocPlot the ROC curve using the sparse thresholdSummary data...
plotVariableScatterplotPlot the variable importance scatterplot
plpDataSimulationProfileA simulation profile
positiveLikelihoodRatioCalculate the positiveLikelihoodRatio
positivePredictiveValueCalculate the positivePredictiveValue
predictCyclopsCreate predictive probabilities
predictPlppredictPlp
preprocessDataA function that wraps around...
recalibratePlprecalibratePlp
recalibratePlpRefitrecalibratePlpRefit
runMultiplePlpRun a list of predictions analyses
runPlprunPlp - Develop and internally evaluate a model using...
savePlpAnalysesJsonSave the modelDesignList to a json file
savePlpDataSave the cohort data to folder
savePlpModelSaves the plp model
savePlpResultSaves the result from runPlp into the location directory
savePlpShareableSave the plp result as json files and csv files for...
savePredictionSaves the prediction dataframe to RDS
sensitivityCalculate the sensitivity
setAdaBoostCreate setting for AdaBoost with python...
setCoxModelCreate setting for lasso Cox model
setDecisionTreeCreate setting for the scikit-learn 1.0.1 DecisionTree with...
setGradientBoostingMachineCreate setting for gradient boosting machine model using...
setIterativeHardThresholdingCreate setting for lasso logistic regression
setKNNCreate setting for knn model
setLassoLogisticRegressionCreate setting for lasso logistic regression
setLightGBMCreate setting for gradient boosting machine model using...
setMLPCreate setting for neural network model with python
setNaiveBayesCreate setting for naive bayes model with python
setPythonEnvironmentUse the virtual environment created using configurePython()
setRandomForestCreate setting for random forest model with python (very...
setSVMCreate setting for the python sklearn SVM (SVC function)
simulatePlpDataGenerate simulated data
sklearnFromJsonLoads sklearn python model from json
sklearnToJsonSaves sklearn python model object to json in path
specificityCalculate the specificity
splitDataSplit the plpData into test/train sets using a splitting...
toSparseMConvert the plpData in COO format into a sparse R matrix
validateMultiplePlpexternally validate the multiple plp models across new...
viewDatabaseResultPlpopen a local shiny app for viewing the result of a PLP...
viewMultiplePlpopen a local shiny app for viewing the result of a multiple...
viewPlpviewPlp - Interactively view the performance and model...
OHDSI/PatientLevelPrediction documentation built on April 6, 2024, 11:50 p.m.