Diagnose via a Single Algorithm

Applies a specified set of diagnostic criteria to a data matrix representing patient-level data to determine whether each patient meets the criteria for probable Parkinson’s disease dementia (PDD). This function is intended to be used internally by the wrapper function diagnose_pdd_sample.

Usage

diagnose_pdd_case(x, c)

Arguments

x

A data frame or matrix containing patient-level variables used for diagnosis.

c

A named vector (or single-row data frame) specifying the criteria to be applied for PDD diagnosis.

Value

A logical vector indicating probable PDD diagnosis for each patient (TRUE = diagnosed, FALSE = not diagnosed).

See also

diagnose_pdd_sample() wraps the function to diagnose all patients.

Examples

if (FALSE) { # \dontrun{
p <- data_paths("data-raw")
data <- prepare_data(p)
crit <- specify_criteria()
pdd  <- diagnose_pdd_case(data, crit[1, ])
} # }