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Healthcare data is notoriously “messy.” ClosedLoop makes it simple to import raw healthcare data sets, such as medical claims, prescriptions, EMR, and custom data, without the need for tedious data normalization and cleansing. Data handling capabilities include:
After data cleansing, feature engineering is one of the most expensive and time-consuming aspects of data science. ClosedLoop helps healthcare data scientists build models and features smarter and faster—freeing them to focus their time on discovery of new insights. Automated feature engineering capabilities include:
ClosedLoop provides data scientists with the tools they need to build highly accurate models and to continuously improve those models as new data and insights are surfaced. The following are just a few of ClosedLoop’s capabilities that directly drive accuracy in healthcare predictive models:
ClosedLoop provides data scientists with the tools they need to build highly accurate models and to continuously improve those models as new data and insights are surfaced. The following are just a few of ClosedLoop’s capabilities that directly drive accuracy in healthcare predictive models:
