Machine Learning for Healthcare Just Got Easier

The software is designed to streamline healthcare machine learning by including functionality specific to healthcare, as well as simplifying the workflow of creating and deploying models.

Everything you need to get started

What Can I Do with

  • Create and compare models based on your data.
  • Save and deploy a model.
  • Perform risk-adjusted comparisons.
  • Improve sparse data via longitudinal imputation.
  • Fill in missing data via imputation.
  • Deploy a model to produce daily predictions.
  • Write predictions back to a database.
  • Learn what factors drive each prediction.

How Is it Tailored to Healthcare?

  • Longitudinal machine learning via mixed models.
  • Longitudinal imputation.
  • Risk-adjusted comparisons.


Our goal with this project is to expedite adoption of ML in healthcare by building pragmatic world class tools to help anyone with access to healthcare data.

How Do I Get Started? is available in packages for both R and Python, two of the most common languages used by data scientists. If you don’t previous experience with either language, we recommend the R package as it currently has more features and R is more newbie-friendly.


Let's do this!

Access documentation, installation instructions, feature references, as well as hints and tips.

How does focus on healthcare?
Both packages differ from other machine learning packages in that they focus on data issues specific to healthcare. This means that we pay attention to longitudinal questions, offer an easy way to do risk-adjusted comparisons, and provide easy connections and deployment to databases.
Who is designed for?
While data scientists in healthcare will likely find these packages valuable, the audience targets are those analysts, BI developers, and SQL developers that would love to create appropriate and accurate models with healthcare data.