Intel Capital invests $10 million in medical artificial intelligence

Chipmaker said that Lumiata will use the money to drive predictive analytics to improve risk and care management for organizations practicing population health. 
By Jack McCarthy
09:37 AM

Intel Capital injected $10 million into Lumiata, an analytics startup that focuses on medical artificial intelligence, the companies said. 

Lumiata will be working on predictive analytics and artificial intelligence to improve risk and care management for organizations embracing population health management to ultimately drive more personalized care.

“By integrating new data streams, such as IoT, with traditional clinical data, Lumiata has the potential to bring a fresh approach to managing risk with healthcare analytics,” Intel Health and Life Sciences general manager Steve Agritelley said in a statement.

[Innovation Pulse: AI, cognitive computing, machine learning are coming. Best time to invest?]

Lumiata said its Medical Graph combines data science with medical science and literature to model human pathophysiology to create the Lumiata Risk Matrix.

The Lumiata Medical Graph is comprised of more than 260 million data points, 4TB of structured and unstructured medical knowledge and 35,000 hours of physician review. The graph uses a variety of data types ranging from claims and EHR data to laboratory results and sensor readings, developed against an expanding data repository of more than 60 million patient lives.

Lumiata said its technology is utilized by a number of leading organizations, including Universal American, Google, and a major BlueCross plan.

Intel Capital led this Series B round with participation from Blue Cross Blue Shield Venture Partners, Sandbox Industries and Khosla Ventures. Lumiata has raised $20 million in total to date.

Twitter: @HealthITNews


Like Healthcare IT News on Facebook and LinkedIn

Want to get more stories like this one? Get daily news updates from Healthcare IT News.
Your subscription has been saved.
Something went wrong. Please try again.