Intel funds healthcare AI specialist Lumiata with $10 Million
June 2, 2016
Predictive analytics and medical AI developer Lumiata has raised $10 million in financing led by Intel Capital. Lumiata is currently expanding the deployment of medical artificial intelligence designed to improve risk and care management for payers, physicians and population health organisations.
"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," said Steve Agritelley, General Manager of the Health and Life Sciences Group at Intel.
In addition to Intel, the company's investors include Blue Cross Blue Shield Venture Partners, Sandbox Industries, and Khosla Ventures.
Lumiata's technology and approach to analytics is designed to allow organisations to identify and manage risk with the precision, efficiency and transparency needed to deliver on value-based care.
Combining data science with medical science and literature, the Lumiata Medical Graph aims to model human pathophysiology. The company's flagship product, the Lumiata Risk Matrix provides the current and evolving risk of each individual within a population through precise, time-based predictions coupled with medical reasoning.
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 utilises 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's technology is utilised by a number of leading organisations, including Universal American, Google, and a major BlueCross plan.
"By merging AI with data science and clinical medicine, we've made breakthrough improvements in the precision and usability of predictive analytics in healthcare," said Ash Damle, CEO and founder of Lumiata. "Generating high-quality predictions with detailed clinical rationale gives users the confidence to act and ultimately capture meaningful value from their data."