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There’s no telling which of these cohorts will most influence AI’s future. Artificial intelligence is like no technology before it; it’s the first technology in history that can evolve without human assistance, and so is wildly unpredictable. Yet while many of these AI companies won’t survive, the players on this list – as a whole – will profoundly reshape technology, not to mention education, the arts, retail and the entirety of culture. The end result of it all? Let’s keep our fingers crossed.
Jason Fish, M.D., chief medical officer with UT Southwestern ACO in the Dallas-Fort Worth area, spoke about working with a machine learning company called ClosedLoop. They are working to reduce unplanned hospital admissions among patients who receive complex care management by using a machine learning platform the ACO developed to help predict patients likely to incur a preventable event such as unplanned hospital admissions, emergency department high utilization, or death.
LTC ACO, an accountable care organization for Medicare beneficiaries who reside in long-term care (LTC) facilities and a ClosedLoop customer, has had success in the Medicare Shared Savings Program. Jason Feuerman, the ACO’s president and CEO, recently spoke with Healthcare Innovation about how the ACO succeeds by “waking up the ecosystem” with data.
Welcome to another installment in our market map series, a collaborative project mapping emerging opportunities in tech. This deep dive into Digital Healthcare Infrastructure features 90+ companies building in the space, 60 active investors and insights from founders, investors and thought leaders.
Artificial Intelligence (AI) is at the forefront of healthcare innovation. AI in healthcare enhances medical treatment and patient experiences, from faster diagnosis to robot-assisted operations. It improves healthcare workers' ability to better identify the day-to-day patterns and requirements of the patients they care for, allowing them to provide better feedback, assistance, and support for good health.
ClosedLoop.ai, healthcare’s data science platform, today announced another year of exceptional growth. In 2021, ClosedLoop established itself as the leader in predictive AI for healthcare by winning the largest healthcare-focused AI challenge ever, quadrupling its revenue year-over-year, more than doubling its customer base and employee headcount, and winning several high-profile industry awards.
Olive, the automation company creating the Internet of Healthcare, today announced a partnership with ClosedLoop, a healthcare data science platform that makes it easy for healthcare organizations to use AI to improve outcomes and reduce costs. ClosedLoop has also joined The Library, a first-of-its-kind universal marketplace for healthcare solutions, to provide AI-enabled predictive analytics to deliver better patient outcomes, such as reducing unplanned hospitalizations, readmission rates and hospital-acquired infections.
ClosedLoop.ai, healthcare’s data science platform, today announced a partnership with Southwestern Health Resources (SWHR), a national leader in population health management. ClosedLoop’s explainable artificial intelligence (AI) helps SWHR enhance its analytics capabilities to predict and reduce unplanned hospitalizations, and better identify and understand the unique needs of patients, so it can continue to set the industry standard for population health management.
ClosedLoop.ai, healthcare’s data science platform, today announced a $34 million Series B financing. The investment round, led by Telstra Ventures with participation from Breyer Capital, Greycroft Ventures, .406 Ventures, and Healthfirst, positions ClosedLoop to extend its lead in delivering artificial intelligence (AI) solutions that tackle some of healthcare’s biggest challenges.
ClosedLoop.ai, healthcare’s data science platform, today announced a new relationship with Palm Beach Accountable Care Organization (PBACO), one of the nation’s leading and most successful physician-led ACOs in the Medicare Shared Savings Program (MSSP).
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.
KLAS examines the recent AI purchase decisions of 47 organizations to determine which vendors are being considered and chosen, which are being replaced, and why provider and payer organizations choose the AI solutions they do (technology? service? healthcare expertise?).
