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ClosedLoop.ai raises $11M Series A funding to help healthcare organizations use data science to improve quality and reduce costs | Tech News | Startups News

ClosedLoop.ai, an Austin, Texas-based healthtech startup that uses AI to identify at-risk patients and recommend the best interventions for each individual, today announced it has closed $11 million Series A to help healthcare organizations improve clinical and financial outcomes. The round was co-led by Greycroft and .406 Ventures with participation from Silicon Valley Bank and Meridian Street Capital.

Founded in 2017 by Andrew Eye and Dave DeCaprio, ClosedLoop makes it easy and affordable for healthcare organizations to use data science to improve outcomes and reduce costs by combining an intuitive end-to-end machine learning platform for data scientists with a catalog of healthcare-specific predictive models and features. In 2017, one of ClosedLoop users, Medical Home Network, used machine learning and artificial intelligence (AI) to more effectively identify high-risk patients that need targeted preventive care.

ClosedLoop’s platform provides leading-edge AI tools and automation capabilities enabling data scientists to build and deploy accurate and explainable predictive models with speed and ease. The platform supports data science teams with healthcare-specific tools for data prep, automated feature engineering, AutoML / model training, and deployment / MLOps. Customers have the ability to build their own advanced custom models using ClosedLoop’s exclusive content library or take off the shelf models and customize them as their own.

ClosedLoop’s content library provides more than 2,000 healthcare features including medication adherence, frailty, co-morbidities, and more, and the industry’s best collection of extendable pre-built predictive and prescriptive models for common healthcare use cases. The pre-built features and AutoML capabilities provide a low-code option for organizations without internal data science expertise, while the ClosedLoop API allows for advanced users to leverage ClosedLoop’s capabilities within the tools they already use such as Python and Jupyter Notebooks.

“The biggest challenges in data science and artificial intelligence are in upfront data wrangling and last-mile deployment and monitoring,” said Andrew Eye, CEO, and Co-Founder of ClosedLoop. “By providing an end to end platform purpose-built for healthcare and the industry’s largest catalog of prebuilt models and features, we allow customers to go from raw, messy healthcare data to production-ready predictive models in as little as 24 hours.”

The disruption of fee-for-service healthcare is reshaping the industry, rapidly becoming a value-based system centered on individuals, prevention, and the management of the chronic disease. Healthcare organizations have struggled to utilize artificial intelligence to their advantage leaving many to use black-box solutions that are not optimized for their patients.

ClosedLoop’s purpose-built, healthcare-focused AI platform helps organizations anticipate some of healthcare’s biggest challenges – such as disease progression, readmissions, hospital infections, and avoidable hospitalizations – and surfaces specific insights that support physicians, health plans, and life science companies to design and deliver services that improve the health of individuals and populations. The platform’s pre-built predictive model templates make it easy for organizations to identify and target opportunities for improving health, delivering high-quality care, and reducing costs.

“Physicians are being asked to do more than ever before. With advanced technology, ClosedLoop brings innovative AI models to clinical workflows with a 100% deployment rate and continues to positively impact the future of practices and improve patient outcomes,” said Ian Sigalow, Co-founder and Partner of Greycroft. “We are excited to invest in ClosedLoop as they expand their platform and support healthcare organizations with the power of artificial intelligence.”


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