Yhat's ScienceOps Solves Language Incompatibilities between Artificial Intelligence Algorithms and Digital Applications
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.
"Lumiata's AI-powered models are built over massive and extremely complex data sets, which need to be continuously tested and refined to ensure precise and clinically-relevant risk predictions. Yhat has enabled us to iterate, fine-tune and deploy our models more efficiently, while working within a secure environment," says Kim Branson, Chief Data Scientist at Lumiata. "ScienceOps runs on premise, behind our firewall, so we are able to maintain full HIPAA compliance and provide our customers with the most secure and accurate risk predictions via our API."
Yhat is a Brooklyn based company whose goal is to make data science applicable for developers, data scientists, and businesses alike. The company provides a software platform for deploying and managing predictive algorithms as REST APIs, while eliminating the painful engineering obstacles associated with production environments like testing, versioning, scaling and security. Yhat is composed of entrepreneurs, data scientists, and engineers formerly at OnDeck, AppNexus, Guidespark, Shareablee, NYMag and Volvo. For more information, visit www.yhat.com or follow on Twitter at @YhatHQ.
Lumiata is a predictive analytics company that leverages medical artificial intelligence to enable health organizations to manage risk and prioritize care. The Lumiata Risk Matrix delivers precise, clinically-relevant predictions on individual risk over specific timeframes, with accompanying medical evidence. The company's core technological engine is the Lumiata Medical Graph, which analyzes hundreds of healthcare data sets within the context of clinical practice and the world's medical knowledge, and maps out insights on current and future health trajectories of individuals. Founded in 2013 and based in Silicon Valley, Lumiata's team is comprised of clinicians, data scientists, and experts in care delivery. For more information, visit www.lumiata.com or follow @lumiata.
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