''For many priority health conditions the challenge is not a lack of treatment options but the ability to proactively and accurately determine what the most effective treatment is, who should deliver this treatment and when it should be initiated''
HEALTH[at]SCALE was founded in 2015 to solve the problem of bringing precision delivery to precision medicine.
We are on a mission to match the world’s patients to the right treatments by the right providers at the right times, at critical points across the care continuum, using specialized advances in predictive machine intelligence.
Our company is led by a world-renowned team of machine learning and clinical faculty out of MIT, Harvard, Stanford and U-Michigan. Our team has provided thought-leadership to the healthcare artificial intelligence and machine learning space for the last two decades; and has deep expertise in predictively optimizing complex care decisions both at the individual and the system-level.
HEALTH[at]SCALE’s platform and applications integrate fundamental advances in artificial intelligence and machine learning for deeply personalized prediction using information in often noisy, fragmented and longitudinally-evolving healthcare datasets. From addressing data quality issues, to learning highly accurate models capable of dealing with complex multi-factorial data, to scalable and secure software-as-a-service (SaaS) applications that can be hosted on-premise or in the public cloud to deliver predictive precision recommendations at points of care, our solutions are designed from the ground up for maximum operational healthcare impact.
Our specialized machine intelligence technologies have been demonstrated in prospective studies with leading payers and providers to significantly improve outcomes and costs. Use of the company’s platform and applications is rapidly growing, with the company’s solutions among the largest deployments to date of machine learning for healthcare, helping payers and providers manage tens of millions of individuals in live production settings.