‘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 date
1 July 2021
Duration
36 months
Application deadline
Funding information

Tax free stipend for 36 months at UKRI rate.

UK/EU tuition fee waiver.

Funding source
National Institute of Health Research (NIHR) and Kent, Surrey, Sussex ARC
Supervised by

About

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.

Eligibility criteria

Essential

  • 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

Desirable

  • 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.

How to apply

Applications should be submitted through the PhD Biosciences and Medicine course page. Applicants are advised to contact the primary supervisor Kamalan Jeevaratnam, for informal enquiries before applying for the studentship.


Application deadline

Contact details

Kamalan Jeevaratnam
01 VSM 02
Telephone: +44 (0)1483 682395
E-mail: k.jeevaratnam@surrey.ac.uk

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