Exemplar Project:
Development of AI to Automatically Identify Inherited Cardiovascular Condition Patients, Enhance Risk Stratification, and Expedite Genetic Testing
Many inherited cardiac conditions (ICCs) go undiagnosed in early stages due to a lack of symptoms, with catastrophic outcomes often being the first indication. Patients are not being identified from routinely collected NHS data, such as ECGs, blood tests, and imaging. Access to specialist care, including genetic testing and family screening, depends heavily on clinicians recognising ICCs and initiating referrals, leading to inequities. Additionally, clinical pathways are inefficient, with tests performed across various settings and times, complicating risk stratification and care coordination.
Project Overview
This project aims to develop and deploy AI tools at KCH and GSTT to identify patients with ICCs, streamline specialist reviews, and improve genetic testing and family screening. It will also enhance risk stratification by integrating clinical, genetic, imaging, and electrophysiological data, supporting personalised treatment and monitoring. The project will evaluate AI’s effectiveness in patient identification, address barriers to diagnosis, and propose improvements to clinical pathways while building a comprehensive dataset for care delivery and research.
National benefit
This project aims to use an open-source code to automatically identify patients, place them on the correct pathway to provide earlier treatment and provide critical data on the utility of AI models in NHS Genomic Medicine Services.
For more information, contact the team:
Antonio deMarvao, Project Lead – antonio.deMarvao@gstt.nhs.uk