Development of a novel AI model for cardiovascular disease risk prediction by analysing retinal vascular structure and functional changes in blood flow

Description

The Department of Eye and Vision Sciences at the University of Liverpool is inviting PhD candidates who are highly motivated in developing novel risk prediction model of cardiovascular disease (CVD) by analysing retinal images, contributing to a better understanding of relationship between the cardiovascular disease and the functional changes in blood flow.

The retina is one of the most metabolically active organs in the body critically supported by ocular blood flow, while CVD is a leading cause of morbidity and mortality worldwide. We aim to develop advanced AI models for analysing the dynamic retinal function, providing a comprehensive analysis of blood flow changes. Multi-modality data will be employed in this project, including imaging data (e.g., color fundus photography, fundus fluorescein angiography) and non-imaging data (e.g., electronic health records). The research will delve into the intersection between AI and healthcare, developing new approaches to revolutionise our understanding of the relationship between retinal vascular structure, blood flow dynamics, and CVD.

The successful PhD candidate will benefit from working with a multidisciplinary team in which there exists extensive experience in the areas of computer science, image processing, high performance computing, mathematics, and medicine.  The work to be undertaken will be conducted at the University of Liverpool as a collaboration between the computer vision scientists (Dr Zhao, Prof Zheng) and clinical experts in CVDs and ophthalmology (Prof Lip, Dr Madhusudhan, Dr Lip). Training will be provided to learn the clinical background and the machine learning algorithm.

Candidate requirements

  1. Being self-motivated and enthusiastic about AI for health
  2. Having an Honours Degree at 2.1 or above (or equivalent) in Mathematics, Engineering, Physics or Computer Science.
  3. Good background knowledge in mathematics/statistics, machine learning, computer programming (Python, C++, etc.)
  4. Having an IELTS score of 6.5 (with no band below 5.5) or equivalent for those whose first language is not English.

Applications

To apply please insert “[PhD application]” and send your CV and a covering letter to He Zhao (he.zhao@liverpool.ac.uk)

Availability

Open to UK applicants

Funding information

Funded studentship

Stipend (approx): £20,000 per annum tax-free, full UK home tuition fees and research bench fees paid. Exact amount TBC. Overseas applicants are welcome to apply, but they must be able to fund the difference between home fees and overseas fees themselves/through additional funding.

Supervisors

References

  1. Ørskov, Marie, et al. "Similarities and differences in systemic risk factors for retinal artery occlusion and retinal vein occlusion: A nationwide case–control study." International ophthalmology 43.3 (2023): 817-824.
  2. Liao, Dingying, et al. "Changes in foveal avascular zone area and retinal vein diameter in patients with retinal vein occlusion detected by fundus fluorescein angiography." Frontiers in Medicine 10 (2023).
  3. Zhao, Aidi, et al. "Optimization of retinal artery/vein classification based on vascular topology." Biomedical Signal Processing and Control 88 (2024): 105539.