ClosedLoop raises $34 million to infuse data science into healthcare
The company’s software combines machine learning with a library of healthcare-specific training features and model templates. The platform integrates several data science workflows — including data onboarding and normalization, automated feature engineering, autoML and MLOps — and includes features that facilitate experimentation, collaboration, oversight and management.
ClosedLoop aims to make machine learning accessible to organizations that lack people with data science backgrounds. Its content catalog enables nontechnical people to create and deploy customized and explainable AI-based solutions quickly, the company said. The ability to explain how machine learning models function is critical in regulated industries such as healthcare.
Healthcare has been a primary target industry for companies building AI software because of the high cost of care and the large amount of wast. The U.S. spends more on health care than any other country and studies have estimated that up to 30% of health care spending is unnecessary.
Applying artificial intelligence to diagnosis and treatment has proven to be a tough problem to crack because of the complexity of clinical analysis. IBM Corp. has had well-publicized difficulties executing its campaign to make its Watson supercomputer a digital assistant to clinicians. It took a black eye when M.D. Anderson Cancer Center abandoned an effort to use Watson as an advisory tool for oncologists in 2016 after sinking $62 million into the venture.
ClosedLoop’s approach to machine learning does away with risk scoring in favor of personalized forecasts delivered directly into clinical workflows, the company said. It can use any data that be linked to individual patients, including electronic health records, medical insurance claims, prescription claims, social determinants of health, lab values and wearable data, said Chief Executive Andrew Eye. Forecasts use patient-specific data to identify variables that explain a person’s risk and links to specific interventions and preventive measures.
One example of outcomes the company has achieved is the COVID-19 vulnerability index that ClosedLoop released to open source last year. It was used by Medical Home Network in Chicago to prioritize resources for those who were most vulnerable prior to vaccine development, Eye said. “Over 10 million patients benefited from the C-19 index thanks in large part to our releasing it as open source,” he said.
Other use cases include predicting avoidable hospitalizations, predicting chronic kidney disease, reducing unplanned hospital admissions, reducing the risk of heart failure and assessing the risk that a patient will develop diabetes.
ClosedLoop said its annual revenue has quintupled since its first funding round two years ago but provided no specifics. The latest round was led by Telstra Ventures Pty Ltd. with participation from Breyer Capital, Greycroft Ventures LLC, .406 Ventures LLC, and Healthfirst Corp. Private investors include former Landmark Health LLC CEO Adam Boehler and former IBM CEO Sam Palmisano.
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