Description Usage Arguments Value Examples
The function requires as input: * a surrogate, such as the ICD code * the healthcare utilization It can leverage other EHR features (optional) to assist risk prediction.
1 2 3 4 5 6 7 8 | PheNorm.Prob(
nm.logS.ori,
nm.utl,
dat,
nm.X = NULL,
corrupt.rate = 0.3,
train.size = 10 * nrow(dat)
)
|
nm.logS.ori |
name of the surrogates (log(ICD+1), log(NLP+1) and log(ICD+NLP+1)) |
nm.utl |
name of healthcare utilization (e.g. note count, encounter_num etc) |
dat |
all data columns need to be log-transformed and need column names |
nm.X |
additional features other than the main ICD and NLP |
corrupt.rate |
rate for random corruption denoising, between 0 and 1, default value=0.3 |
train.size |
size of training sample, default value 10 * nrow(dat) |
list containing probability and beta coefficient
1 2 3 4 5 6 7 8 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.