A stitch in time saves nine, they say — and a blood thinner in time saves a trip to the emergency room for a heart attack, as Diagnostic Robotics hopes to show. The company’s machine learning-powered preventative care aims to predict and avoid dangerous (and costly) medical crises, saving everyone money and hopefully keeping them healthier in general — and it has raised $45 million to scale up. “We see how people look before the problems — everything we do is preventative care,” said Kira Radinsky, CEO and co-founder of Diagnostic Robotics. It’s important to explain at the start that this particular combination of AI, insurance, hospital bills and “predictive medicine” isn’t some kind of technotopian nightmare. The AI will already have done its work, and maybe your test results and location suggest you’re at risk for something — and you’d do well to take these recommendations seriously. The Tel Aviv-based Diagnostic Robotics just raised a $45 million B round, led by StageOne investors, with participation from Mayo Clinic, Technion (Israel Institute of Technology) and Bradley Bloom. “You’ll get phone calls from care managers offering additional treatments, for free or almost for free,” Radinsky said. The whole company is based on the fact that it’s both better for you and cheaper if you, for example, improve your heart health rather than have a heart attack. (TechCrunch). Continue reading.
Researchers have used deep learning to model more precisely than ever before how ice crystals form in the atmosphere.
A stitch in time saves nine, they say — and a blood thinner in time saves a trip to the emergency room for a heart attack, as Diagnostic Robotics hopes to show.
We interviewed him to discuss why machine learning is such a good fit for healthcare, how it has helped to date with diagnosis and coding, and, most important, what is holding it back in healthcare.