Measuring QRISK-3 risk score based on NLP on electronic health records

  • Applicant: Tao Wang
  • Project ID: 19-051

The QRISK-3 algorithm has been widely validated in calculating a person’s risk of developing a heart attack or stroke over the next 10 years, which helps enable doctors to identify those at most risk of heart disease and stroke. However, due to a wide range of variables/predictors in use, clinicians need to go through a large number of electronic health records (EHR) to calculate a QRISK-3 score, which limits the practical usage of this score in clinical settings. This project will investigate using natural language processing (NLP) techniques to automatically extract predictors from EHR.

The Clinical Record Interactive Search (CRIS) system is a computer system that allows researchers at the NIHR Maudsley Biomedical Research Centre (BRC) to carry out research using information from South London and Maudsley NHS Foundation Trust clinical records.

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The Clinical Record Interactive Search has been developed in collaboration with:

South London and Maudsley NHS Foundation Trust
NIHR Maudsley BRC