BROOKLYN, N.Y., Nov. 15, 2016 /PRNewswire/ -- Yhat, a software company working to bridge the technological divide between data scientists and engineers, announced today that Lumiata, the AI-powered predictive analytics company, has implemented Yhat's machine learning deployment platform, ScienceOps.
Lumiata is using ScienceOps to incorporate its proprietary health risk algorithms into their predictive tool, the Risk Matrix. The Lumiata Risk Matrix delivers personalized, time-based predictions of an individual's future health state based on associated clinical conditions or diagnoses, and is delivered via an API. By leveraging Yhat's ScienceOps, Lumiata's data science and engineering teams can efficiently work with large health data sets to develop and deploy models that deliver individual and population-level risk predictions. "Companies in med tech are pioneering all kinds of new AI innovations to provide better care for individuals," said Austin Ogilvie, CEO and co-founder 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. Our hope is that we can help the companies launching these AI driven applications, and ultimately have a positive impact on the health and well-being of their patients." ScienceOps allows data scientists and engineers to work together to build apps powered by predictive analytics. Typically, data scientists' open source statistical tools are technically incompatible with the frameworks and languages developers use to build apps. ScienceOps bridges this gap, allowing teams to leverage advanced algorithms written in R and Python directly within web and mobile apps, and to do so rapidly, securely, and at scale.