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While many people know machine learning as the technology that drives some consumer applications, like personal digital assistants Siri and Alexa, it’s also used by healthcare providers to extract value from vast quantities of patient charts and other documents to inform operations and care delivery.

Implementing machine learning-driven solutions gives healthcare organizations the potential to access previously untapped patient data, improve operational efficiency and ultimately provide more effective patient care.

Machine learning has the potential to dramatically change how healthcare is delivered by providers and how patients receive care, but it’s only as effective as the data we’re able to access and analyze.

While unstructured data contains critical details about patient health, conditions, past family history and treatments, it’s largely gone unused by payers and providers because it’s much more challenging to access and for computers to analyze.

A recent study investigated how machine learning can help healthcare providers measure the quality of care for heart failure patients.

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