Available
Project number:
2025_58
Start date:
October 2025
Project themes:
Main supervisor:
Consultant Cardiologist / Senior Clinical Lecturer
Co-supervisor:
Professor James Teo
Additional Information:
Natural Language Processing for diagnosis and enhanced risk stratification in Inherited Cardiovascular Conditions
Background
Inherited cardiovascular conditions (ICCs), such as hypertrophic cardiomyopathy (HCM),dilated cardiomyopathy (DCM) and inherited arrhythmia syndromes, are genetic disorders that can lead to life-threatening heart problems, heart failure and sudden cardiac death in the young. Diagnosing these conditions early is challenging because symptoms may not appear until later stages, and subtle changes in routine medical tests such as ECGs and heart scans can be overlooked or misattributed to more common conditions. Without early detection, patients may not receive the specialised care needed, which can result in disease progression and worse outcomes.
Novelty & Importance
This project will use machine learning (ML) and natural language processing (NLP) to improve the diagnosis and management of ICCs by analysing routinely collected NHS electronic health records (EHRs) from millions of patients. AI has the ability to detect specific features and complex patterns in clinical, genetic, imaging, and heart rhythm data that may otherwise go unnoticed. By identifying these patterns, AI can help diagnose ICCs earlier, improve the accuracy of risk predictions, and provide tailored treatments for patients. This approach could lead to better outcomes and more efficient use of healthcare resources.
Aims & Objectives
The primary aim of the project is to develop AI-driven models to enhance the early diagnosis and risk stratification of ICCs. The objectives include automatically identifying patients with undiagnosed ICCs from NHS data, integrating clinical and genetic information to predict disease progression, and developing personalized monitoring and treatment plans based on each patient's risk profile.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at