# code to create the json prediction:
populationSettings <- list(PatientLevelPrediction::createStudyPopulationSettings(riskWindowEnd = 30,
riskWindowStart = 1,
washoutPeriod = 365,
removeSubjectsWithPriorOutcome = TRUE,
firstExposureOnly = TRUE,
priorOutcomeLookback = 99999,
requireTimeAtRisk = FALSE),
PatientLevelPrediction::createStudyPopulationSettings(riskWindowEnd = 60,
riskWindowStart = 1,
washoutPeriod = 365,
removeSubjectsWithPriorOutcome = TRUE,
firstExposureOnly = TRUE,
priorOutcomeLookback = 99999,
requireTimeAtRisk = FALSE),
PatientLevelPrediction::createStudyPopulationSettings(riskWindowEnd = 90,
riskWindowStart = 1,
washoutPeriod = 365,
removeSubjectsWithPriorOutcome = TRUE,
firstExposureOnly = TRUE,
priorOutcomeLookback = 99999,
requireTimeAtRisk = FALSE))
modelList <- list(list("LassoLogisticRegressionSettings" = list("variance" = 0.01,
"seed" = 1000)))
covariateSettings <- list(list(list(fnct = 'createCovariateSettings',
settings = FeatureExtraction::createCovariateSettings(useDemographicsGender = T,
useDemographicsAgeGroup = T)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Autoimmune_disease',
covariateId = 22590,
cohortId = 22590,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Atrial_fibrillation',
covariateId = 22591,
cohortId = 22591,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Asthma',
covariateId = 22592,
cohortId = 22592,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Thrombophilia',
covariateId = 22593,
cohortId = 22593,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Antiphospholipid_syndrome',
covariateId = 22594,
cohortId = 22594,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Malignant_neoplastic_disease',
covariateId = 22614,
cohortId = 22614,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Diabetes_mellitus',
covariateId = 22613,
cohortId = 22613,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Obesity',
covariateId = 22612,
cohortId = 22612,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Heart_disease',
covariateId = 22611,
cohortId = 22611,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Hypertensive_disorder',
covariateId = 22618,
cohortId = 22618,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Renal_impairment',
covariateId = 22617,
cohortId = 22617,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Chronic_obstructive_lung_disease',
covariateId = 22616,
cohortId = 22616,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Dementia',
covariateId = 22615,
cohortId = 22615,
startDay=-99999,
endDay=0,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Antiinflammatory',
covariateId = 22606,
cohortId = 22606,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Coxib',
covariateId = 22605,
cohortId = 22605,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Corticosteroids',
covariateId = 22604,
cohortId = 22604,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Antithrombotic_agent',
covariateId = 22603,
cohortId = 22603,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Lipid_modifying_agent',
covariateId = 22610,
cohortId = 22610,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Antineoplastic_immunomodulating',
covariateId = 22609,
cohortId = 22609,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Hormonal_contraceptives',
covariateId = 22608,
cohortId = 22608,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Tamoxifen',
covariateId = 22607,
cohortId = 22607,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)),
list(fnct = 'createCohortCovariateSettings',
settings = list(covariateName = 'Sex_hormones_modulators',
covariateId = 22598,
cohortId = 22598,
startDay=-183,
endDay=-4,
count=F,
ageInteraction = F)))
)
resrictOutcomePops <- NULL
resrictModelCovs <- NULL
executionSettings <- list(minCovariateFraction = 0.000,
normalizeData = T,
testSplit = "stratified",
testFraction = 0.25,
splitSeed = 1000,
nfold = 3)
json <- createDevelopmentStudyJson(packageName = 'CovCoagEmaPrediction',
packageDescription = 'Prediction model based on predictors proposed by the EMA',
createdBy = 'Henrik John',
organizationName = 'Erasmus University Medical Center',
targets = data.frame(targetId = c(22956),
cohortId = c(22956),
targetName = c('Target')),
outcomes = data.frame(outcomeId = c(22601,22600,22599,22595,22596,22602,22933,22954),
cohortId = c(22601,22600, 22599,22595,22596,22602,22933,22954),
outcomeName = c('MI','IS','MI or IS','PE','DVT narrow',
'VTE narrow', 'DTH', 'STR')),
populationSettings = populationSettings,
modelList = modelList,
covariateSettings = covariateSettings,
resrictOutcomePops = resrictOutcomePops,
resrictModelCovs = resrictModelCovs,
executionSettings = executionSettings,
webApi = webApi,
outputLocation = 'D:/hjohn/CovCoagEma',
jsonName = 'predictionAnalysisList.json')
specifications <- Hydra::loadSpecifications(file.path('D:/hjohn/CovCoagEma', 'predictionAnalysisList.json'))
Hydra::hydrate(specifications = specifications, outputFolder = 'D:/hjohn/CovCoagEma/CovCoagEmaPrediction')
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