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PheNorm  

Unsupervised Gold-Standard Label Free Phenotyping Algorithm for EHR Data
View on CRAN: Click here


Download and install PheNorm package within the R console
Install from CRAN:
install.packages("PheNorm")

Install from Github:
library("remotes")
install_github("cran/PheNorm")

Install by package version:
library("remotes")
install_version("PheNorm", "0.1.0")



Attach the package and use:
library("PheNorm")
Maintained by
Clara-Lea Bonzel
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-07
Latest Update: 2021-01-07
Description:
The algorithm combines the most predictive variable, such as count of the main International Classification of Diseases (ICD) codes, and other Electronic Health Record (EHR) features (e.g. health utilization and processed clinical note data), to obtain a score for accurate risk prediction and disease classification. In particular, it normalizes the surrogate to resemble gaussian mixture and leverages the remaining features through random corruption denoising. Background and details about the method can be found at Yu et al. (2018) .
How to cite:
Clara-Lea Bonzel (2021). PheNorm: Unsupervised Gold-Standard Label Free Phenotyping Algorithm for EHR Data. R package version 0.1.0, https://cran.r-project.org/web/packages/PheNorm. Accessed 22 Dec. 2024.
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Complete documentation for PheNorm
Functions, R codes and Examples using the PheNorm R package
Some associated functions: PheNorm.Prob . 
Some associated R codes: PheNorm_Prob.R . VTM.R . findMagicNumber.R . import.R . normalmixEM2comp2.R .  Full PheNorm package functions and examples
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