- Salt Lake City-based Health Catalyst launched an open source repository of machine learning algorithms aimed at advancing medical outcomes through artificial intelligence.
- Healthcare.ai is designed to streamline machine learning by simplifying the process of creating and implementing models. It can also handle longitudinal questions and risk-adjusted comparisons.
- Interested parties can visit the company’s website and install one of two language packages for healthcare data science, R or Python.
Health Catalyst believes that by offering healthcare.ai for free, more health professionals — not just those with data analytics training — will be able to model more effective outcomes for their patient populations.
Dale Sanders, executive vice president of Health Catalyst, said the repository will “democratize” machine learning in healthcare the way it has been in other industries.
Using healthcare.ai, the company has already built a number of predictive models, including for central line-associated blood stream infection, readmission models for chronic obstructive pulmonary disorder, schedule optimization, and propensity to pay, according to the announcement.
The launch follows IBM’s preview of a range of AI and machine learning-driven solutions and physician support tools for use in medical imaging at the Radiological Society of North America annual meeting in Chicago.