Machine Learning in Fabry disease version 1

  • Research type

    Research Study

  • Full title

    Development of a Machine Learning method to diagnose Fabry disease in Cardiology

  • IRAS ID

    305043

  • Contact name

    Duncan Cole

  • Contact email

    duncan.cole@wales.nhs.uk

  • Sponsor organisation

    Cardiff and Vale UHB

  • Duration of Study in the UK

    2 years, 0 months, 1 days

  • Research summary

    Fabry disease is a rare inherited condition affecting many parts of the body, including the heart, kidneys and nerves. It is difficult to diagnose as the problems it causes look similar to lots of other conditions. We are aiming to develop a machine learning approach to diagnosis of Fabry disease using data routinely gathered in hospital cardiology clinics, including from blood tests, ECGs, and echocardiograms. This will use data from tests already completed, which will then be anonymised before it is used. One we have developed a machine learning program to do this, we will test the program by mixing data from patients with Fabry disease and those with another condition and seeing if the program can correctly identify the Fabry patients, and to compare this with a cardiologist's diagnosis.

  • REC name

    N/A

  • REC reference

    N/A