While data scientists in healthcare will likely find this project valuable, the target audience for healthcare.ai are those BI developers, data architects, and SQL developers that would love to create appropriate and accurate models with healthcare data. While existing machine learning packages are certainly irreplaceable, we think that there is a set of data problems specific to healthcare that warrant new tools.
healthcare.ai differs from other machine learning packages in that it focuses 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.
This project began in the data science group at Health Catalyst, a Salt Lake City-based company focused on improving healthcare outcomes.
We believe that everyone benefits when healthcare is made more efficient and outcomes are improved. Machine learning is surprisingly still fairly new to healthcare and we want to quickly take healthcare down the machine learning adoption path. We believe that making helpful, simple tools widely available is one small way to help healthcare organizations transform their data into actionable insight that can be used to improve outcomes.
We'd love to hear from you! We welcome complaints, suggestions, and contributions.
Twitter: @levithatcher Email: [email protected]