Welcome to healthcare.ai
This package will get you started with healthcare machine learning in R.
Find our code at our Github Repo
What can you do with it?
- Create and compare models based on your data.
- Save and deploy a model.
- Perform risk-adjusted comparisons.
- Do trend analysis following Nelson rules.
- Improve sparse data via longitudinal imputation.
How is it specific to healthcare?
- Longitudinal machine learning via mixed models
- Longitudinal imputation
- Risk-adjusted comparisons
For those starting out
Note: if you're setting up R on an ETL server, don't download RStudio--simply open up RGui
Install the latest release on Windows
Open RStudio and work in the console
install.packages('healthcareai')
How to install the latest version on macOS
Open RStudio and work in the console
install.packages('healthcareai')
How to install latest version on Ubuntu (Linux)
- An Ubuntu 14.04 Droplet with at least 1 GB of RAM is required for the installation.
- Follow steps 1 and 2 here to install R
- Run
sudo apt-get install libiodbc2-dev
- Run
sudo apt-get install unixodbc unixodbc-dev
- After typing
R
runinstall.packages('healthcareai')
Install the bleeding edge version (for folks providing contributions)
Open RStudio and work in the console
library(devtools)
devtools::install_github(repo='HealthCatalyst/healthcareai-r')
Tips on getting started
Built-in examples
Load the package you just installed and read the built-in docs
library(healthcareai)
?healthcareai
Website examples
See our docs website
Jupyter notebook examples
If you like Jupyter notebooks, check out step 1 and step 2 in model building with healthcareai.
Join the community
Read the blog and join the slack channel at healthcare.ai
What's new?
The CRAN 1.0.0 release features:
- Added:
- Kmeans clustering
- XGBoost multiclass support
- findingVariation family of functions
- Changed:
- Develop step trains and saves models
- Deploy no longer trains. Loads and predicts on all rows.
- SQL uses a DBI back end
- Removed:
- testWindowCol
is no longer a param.
- SQL reading/writing is outside model deployment.
For issues
- Double check that the code follows the examples in the built-in docs
library(healthcareai)
?healthcareai
-
Make sure you've thoroughly read the descriptions found here
-
If you're still seeing an error, file an issue on Stack Overflow using the healthcare-ai tag. Please provide
- Details on your environment (OS, database type, R vs Py)
- Goals (ie, what are you trying to accomplish)
- Crystal clear steps for reproducing the error
How to help
Check out our github repo.