‘From data to diagnosis’: Identification of patients with atrial fibrillation using computational analysis of sinus rhythm electrocardiograms
We seek to develop predictive algorithms for the detection of paroxysmal atrial fibrillation through the analysis of sinus rhythm ECG using novel computational algorithms.
Start date1 April 2021
Tax free stipend for 36 months at UKRI rate.
UK/EU tuition fee waiver.
Funding sourceNational Institute of Health Research (NIHR) and Kent, Surrey, Sussex ARC
UK prevalence of atrial fibrillation (AF), the most common treatable form of cardiac rhythm disorder seen in clinical practice is expected to rise with the increase in the ageing population. In addition, risk factors for AF, such as hypertension and obesity are expected to increase globally. Importantly, the prevalence of AF is likely underestimated as a large proportion remain undiagnosed due to the transient (paroxysmal) nature of this abnormality. AF can have major consequences if undetected (such as strokes). Our project is based on using several novel computational algorithms on electrocardiographic (ECG) signals to find visually non-discernible differences. We will explore combining the information from the different algorithms to increase the accuracy of the predictions. This project will create a framework that can facilitate accurate and rapid diagnosis of patients and be a stepping stone towards an automated, low cost and reliable screening method for AF and other cardiovascular diseases.
- MSc degree European equivalent degree in a relevant discipline (e.g. biomedical engineering, mathematics, biophysics, computer science, medicine or veterinary medicine)
- Evidence on computational skills/ability – (e.g. R, Matlab, C++, Python)
- Excellent communication and organisational skills
- Ability to work independently and as part of a team
- Previous research publication track record
- Good Clinical Practice (GCP) certified
- Evidence of previous experience preparing for ethical approval for human studies
Available for UK and EU students.
IELTS requirements: 7.0 overall with 6.5 in each band.