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Easily Handle Messy
Healthcare Data.

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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:

  • HIPAA-compliant storage and data access
  • Import bulk and streaming data
  • Support for all major coding systems
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Automate Feature
Engineering.

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  • Comorbidities
  • Durable Medical Equipment
  • Medical Cost Patterns
  • Admissions
  • Visit Counts
  • Medication Adherence
  • Lab Results
  • Charlson Comorbidity Index
  • Stroke Severity Index
  • Frailty Index
  • Delirium Risk Index
  • Hierarchical Condition Categories
  • USDA Food Environment Atlas
  • Continuity of Care Index
  • Area Deprivation Index
  • County Health Rankings
  • CDC Behavioral Risk Factors

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:

  • Over 2,000 prebuilt healthcare-specific features
  • Automatic mappings to licensed ontologies
  • Support for complex combinations of events
  • Fully automated model training and evaluation process
ClosedLoop incompleted logoGold arc on ClosedLoop logo
  • Comorbidities
  • Durable Medical Equipment
  • Medical Cost Patterns
  • Admissions
  • Visit Counts
  • Medication Adherence
  • Lab Results
  • Charlson Comorbidity Index
  • Stroke Severity Index
  • Frailty Index
  • Delirium Risk Index
  • Hierarchical Condition Categories
  • USDA Food Environment Atlas
  • Continuity of Care Index
  • Area Deprivation Index
  • County Health Rankings
  • CDC Behavioral Risk Factors
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Increase Accuracy.

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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:

  • Automated machine learning​
  • Neural networks, Gradient-boosted trees​
  • Hyperparameter optimization​
  • Automated ROC and precision/recall curves
  • Explainability reports  (population and patient)​
  • Cohort / Population Definition
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Enable Seamless Model
Deployment.

seamless model deployment

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:

  • Model hosting and API
  • Prediction audit and governance through stored results​
  • Prediction trends​
  • Versioning of models​ and features
  • Detect drops in predictor performance over time​
  • Error handling for schema changes, etc.​
  • Model ROI reporting
seamless model deployment

Interested in Enhancing Your Data Science Capabilities?

Get in touch today to see the ClosedLoop platform in action.

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