Lumiata, a San Mateo, California, startup that launched in January with the promise of using machine learning to help hospital personnel make better decisions, has added $6 million to its series A round of venture capital. BlueCross BlueShield Venture Partners and Sandbox Industries provided the new financing, which adds to the $4 million that Khosla Ventuers has already invested.
Lumiata’s system ingests millions of data points (170 million to date), including medical literature and individual patient data such as claims and sensor reading, and uses graph analysis techniques to gain a better understanding of a patient’s health at any given time. This kind of data could help hospitals make better decisions about how to treat patients or understand the overall health of the populations they treat As patients come into the emergency room, Lumiata’s technology, which knows a lot about the relationships between symptoms, personal traits and diseases, could help nurses make accurate diagnoses without waiting for a doctor.
Health care is a major focus of attention for tech companies trying to turn their expertise in fields like machine learning into very helpful and very lucrative businesses. A very small sample of these companies include IBM, which has famously been working closely with various medical institutions to help them integrate its Watson cognitive computing system; a deep learning learning startup called Enlitic that wants to analyze medical images in order to diagnose diseases; and a planned spinout form the University of Washington that uses machine learning models to predict the likelihood a patient with cardiovascular disease will be readmitted within 30 days.