Laboratory Data Integration

Fillmore and his colleagues developed an interactive machine learning framework to streamline the categorization of laboratory tests within large electronic health record databases. This approach reduces the manual effort required for clinical concept adjudication, enabling the precise organization of billions of data points across millions of patients. Such advancements facilitate more efficient and transparent secondary research using vast clinical cohorts.