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Knowledge Graph based Phenotyping on Heterogenous Data Sources

Why & What

Extracting patient phenotypes from routinely collected health data (such as Electronic Health Records) requires translating clinically-sound phenotype definitions into queries/computations executable on the underlying data sources by clinical researchers. This requires significant knowledge and skills to deal with heterogeneous and often imperfect data. Translations are time-consuming, error-prone and, most importantly, hard to share and reproduce across different settings. This project implements a knowledge driven phenotyping framework that

  1. decouples the specification of phenotype semantics from underlying data sources;
  2. can automatically populate and conduct phenotype computations on heterogeneous data spaces.

Architecture & Deployment

This framework has been deployed on five Scottish health datasets. alt text