A San Jose-based company focused on machine learning for care optimization, Health[at]Scale, has raised $16 million in a Series A funding round.
The AI company, which boasts former machine learning and clinical faculty from MIT, Harvard, Stanford and University of Michigan, matches patients with the right treatment and provider at the right time through its platform and applications that integrate new machine learning capabilities for personalized prediction for health plans, provider systems and self-insured employers.
The funding is of particular note as the sole investor is Optum, the technology-focused health services business of UnitedHealth Group, TechCrunch reported. Optum is an active investor in the healthcare technology space and created a $250 million venture fund back in 2017 to invest in startup and early-stage companies that aim to advance the healthcare system.
Health[at]Scale’s technology has already grown, and it is among the largest deployed machine learning technologies for enterprise healthcare, according to a press release. Its platform predictively optimizes complex care decisions for better patient outcomes and lower costs.
“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 it and when it should be initiated,” Zeeshan Syed, CEO of Health[at]Scale, said in a statement. “Machine learning is unique in its capacity to enable precision medicine with the necessary precision delivery to maximize impact.”
The funding round underscores the influx of venture money in the AI in healthcare sector and the rising buzz around machine learning technology. Recently, a machine learning-focused dental company scored $11 million in financing.