healthcareai: Tools for Healthcare Machine Learning

Aims to make machine learning in healthcare as easy as possible. You can develop customized, reliable, high-performance machine learning models with minimal code. Models are created with automatic preprocessing, hyperparameter tuning, and algorithm selection (between 'xgboost' Chen, T. & Guestrin, C. (2016) <arXiv:1603.02754>, 'ranger' Wright, M. N., & Ziegler, A. (2017) <doi:10.18637/jss.v077.i01>, and 'glm' Friedman J, Hastie T, Tibshirani R. (2010) <doi:10.18637/jss.v033.i01>) so that they can be easily put into production. Additionally, there are tools to help understand how a model makes its predictions, select prediction threshholds for operational use, and evaluate model performance over time. Code uses 'tidyverse' syntax and most methods have an associated visualization.

install.packages("healthcareai")

Try the healthcareai package in your browser