UW spinout KenSci raises $8.5M for machine learning platform that predicts which patients will get sick
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Healthcare is an expensive industry. Every year, the United States spends about $9,000 per capita on healthcare, higher than in many other industrial countries. And despite that extra spending, U.S. health outcomes aren’t any better than countries that spend less — in some instances, they’re worse.
One way to lower costs and increase quality in the healthcare system would be to predict which patients will get sick, and while predicting the future seems impossible, that’s exactly what data science and machine learning startup KenSci is hoping to do. Today the company announced that it has raised $8.5 million in a Series A investment round, led by Ignition Partners, to kick their program into high gear.
KenSci was spun out of the University of Washington Tacoma in 2015 by two childhood friends — professor Ankur Teredesai, who heads the UW Tacoma’s center for data science, and longtime Microsoft exec Samir Manjure.

Its goal is simple: “We are really on a mission to fight death with data science,” Manjure told GeekWire.
“Underneath that, what we’re doing is building a risk prediction platform for healthcare that helps uncover various kinds of risks, whether those be clinical risks, financial risks, or operational risks,” he said.
“Today the healthcare system is more of a disease management system,” said Sunny Neogi, KenSci head of growth.
Patients come to a hospital when they are sick, they explain their symptoms, and receive treatment. But to be truly effective, health care systems need to be more proactive in identifying which patients will have further complications or will likely develop serious diseases, he said

