Lumiata, a company that leverages artificial intelligence for predictive analytics, has developed a predictive risk tool that delivers individual and population-level risk predictions. The tool, called the Risk Matrix, bases these predictions on individual clinical conditions and large health datasets; however, Lumiata now plans to integrate Yhat’s machine learning deployment platform into the Risk Matrix to expand these services.
Yhat, a software company, developed ScienceOps to solve language incompatibilities between AI algorithms and digital applications. Data scientists’ algorithms are often written in coding languages like R and Python, which are different than the coding languages developers typically use to build mobile apps, according to Yhat. With ScienceOps, the company aims to bridge this divide by transforming statistical code into a language mobile apps can read.
“Companies in med-tech are pioneering all kinds of new AI innovations to provide better care for individuals,” said Austin Ogilvie, CEO and cofounder of Yhat. “We provide the technical infrastructure that companies need to transform statistical code on an analyst’s laptop into a product that you and I can interact with.”
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