The Seattle startup, a spinout from University of Washington Tacoma, is developing a machine-learning technology to help doctors in their work.
Big data has quickly become a buzzword among technologists. It can help businesses better understand what customers like about an app. It can teach a robot to better respond to commands.
And now it may be able to prevent people from getting sick.
Seattle startup KenSci has created a machine-learning technology that helps doctors predict who might get sick and how sick they might get, and take actions to help them before it happens.
The company, a spinout from University of Washington Tacoma, has compiled a system that can scan through hundreds of variables and past examples to help inform doctors’ decisions. The giant machine-learning system also aims to help health clinics cut down on costs by pointing out waste and unneeded resources.
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KenSci announced Wednesday it has raised $8.5 million in a round led by Bellevue firm Ignition Partners. The 20-person company plans to use the funds to quadruple its workforce this year and bring on more customers.
The company mines a variety of patient health records to establish patterns about patients and hospital administrations.
“If we can predict what is going to happen, then we can help prevent it in a timely manner,” CEO and co-founder Samir Manjure said.
KenSci is already working with a dozen health systems on the technology. A few similar companies have popped up in recent year, but Manjure said KenSci’s strength is in its speed.
It can digest information from a health system and start giving insights in as little as 10 weeks.
The data from each health system stays within that system; the private information doesn’t travel from hospital to hospital. But each new data point and example teaches KenSci’s models more and more, and those learnings are applied to every health system.
Besides Ignition Partners, KenSci’s funding round came from Osage University Partners and Mindset Ventures.