PheVis (version 1.0.4)

train_phevis: train_phevis

Description

Global function to train phevis model.

Usage

train_phevis(
  half_life,
  df,
  START_DATE,
  PATIENT_NUM,
  ENCOUNTER_NUM,
  var_vec,
  main_icd,
  main_cui,
  rf = TRUE,
  p.noise = 0.3,
  bool_SAFE = TRUE,
  omega = 2,
  GS = NULL
)

Value

A list

• surparam - the parameters used to compute the surrogate

• model - the random intercept logistic regression

• df_train_result - the data.frame containing the output predictions

• train_param - parameters for the model training (variables used, main ICD and CUIS, half_life, gold standard)

Arguments

half_life

Duration of cumulation. For a chronic disease you might chose Inf, for acute disease you might chose the duration of the disease.

df

data.frame containing all the variables.

START_DATE

Column name of the time column. The time column should be numeric

PATIENT_NUM

Column name of the patient id column.

ENCOUNTER_NUM

Column name of the encounter id column.

var_vec

Explanatory variables used for the prediction, including the main variables.

main_icd

Character vector of the column names of the main ICD codes.

main_cui

Character vector of the column names of the main CUIs.

rf

should pseudo-labellisation with random forest be used (default is true)

p.noise

percentage of noise introduced during the noising step (default is 0.3)

bool_SAFE

A boolean. If TRUE, SAFE selection is done, else it is not (default is TRUE)

omega

Constant for the extrema population definition (default is 2)

GS

Character string corresponding to the name of the gold-standard variable (default is null for which a vector of 0 will be taken).

Examples

library(dplyr)
PheVis::data_phevis
df <- data_phevis %>%
         mutate(ENCOUNTER_NUM = row_number(),
         time = round(as.numeric(time)))
model <- PheVis::train_phevis(half_life = Inf,
         df = df,
         START_DATE = "time",
         PATIENT_NUM = "subject",
         ENCOUNTER_NUM = "ENCOUNTER_NUM",
         var_vec = c(paste0("var",1:10), "mainCUI", "mainICD"),
         main_icd = "mainICD",
         main_cui = "mainCUI")