See the following -

Health Catalyst Launches Open Source Machine Learning:

Press Release |, Health Catalyst | December 1, 2016

Use of machine learning and predictive analytics to improve health outcomes has so far been limited to highly-trained data scientists, mostly in the nation's top academic medical centers. No longer. is on a mission to make machine learning accessible to the thousands of healthcare professionals who possess little or no data science skills but who share an interest in using the technology to improve patient care. By making its central repository of proven machine learning algorithms available for free, enables a large, diverse group of technical healthcare professionals to quickly use machine learning tools to build accurate models...

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Open Source is Helping to Drive the Artificial Intelligence Renaissance

Sam Dean | Ostatic Blog | January 4, 2017

We're only a few days into 2017, and it's already clear that one of the biggest tech categories of this year will be artificial intelligence. The good news is that open source AI tools are proliferating and making it easy for organizations to leverage them. AI is also driving acquisitions. As Computerworld is reporting, in the past year, at least 20 artificial intelligence companies have been acquired, according to CB Insights, a market analysis firm. MIT Technology Review is out with its five big predictions for AI this year. Here is a bit on what they expect, and some of the open source AI tools that you should know about...

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Open Source Libraries for Health Analytics

Andy Oram | EMR & HIPAA | December 19, 2016

According to Health Catalyst’s Director of Data Science Levi Thatcher, the main author of the project, these tools are tried and tested. Many of them are based on popular free software libraries in the general machine learning space: he mentions in particular the Python Scikit-learn library and the R language’s caret and and data.table libraries. The contribution of Health Catalyst is to build on these general tools to produce libraries tailored for the needs of health care facilities, with their unique populations, workflows, and billing needs. The company has used the libraries to deploy models related to operational, financial, and clinical questions. Eventually, Thatcher says, most of Health Catalyst’s applications will use predictive analytics based on, and now other programmers can too...

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