Tele-ophthalmology & AI to enable referral between community & hospitals for retinal disease

Now closed

Tele-ophthalmology-enabled and Artificial Intelligence-ready referral between community optometry and hospital-based eye clinics for retinal disease

This is a 4-year award co-funded by UCL Department of Computer Science and the Moorfields BRC. The successful candidate will be enrolled in the EPSRC Centre for Doctoral Training in Intelligent, Integrated Imaging in Healthcare (i4health). 

UCL Supervisor: 

Prof Ann Blandford 

Moorfields Supervisor: 

Dr Konstantinos Balaskas 

Background: 

Hospital eye clinics receive a very large number of referrals for patients who had an eye check-up at a high street optometrist. Of those a significant proportion relate to problems with the retina. The best way to detect problems of the retina is by doing a quick, non-invasive scan called Optical Coherence Tomography (OCT). Increasingly, high street opticians are equipped with this technology, but there is a shortage of trained staff for interpreting these scans. The result can be a ‘deluge’ of referrals that overwhelm hospital eye clinics and delay access to care for patients that do require treatment. Recently, revolutionising technology based on Artificial Intelligence and tele-ophthalmology has been developed that can read OCT scans in an automated way and/or by a specialist and offer advice on whether a referral to hospital clinics is needed and how urgently. 

This research project aims to investigate the facilitators and barriers to implementing the AI and tele-ophthalmology platform at scale. The project will involve a number of high street optometry practices with OCT that refer patients to hospital based clinics, as well as two hospital based clinics. 

Project plan: 

The detailed project plan will be developed in collaboration with the student recruited to the position, so as to build on the skills and interests of the student as well as those of the 

current project team. It will involve qualitative or mixed methods, potentially including observations of consultations and other relevant clinical work, interviews with patients and health professionals, and prototyping and testing of novel interfaces to the platform. 

Requirements: 

Applicants are expected to have a first degree in computing, psychology or a design discipline (First class or 2(i) Honours), and will ideally also have a Masters in Human–Computer Interaction or a closely related discipline. They will also have an interest in Artificial Intelligence applications in healthcare, and experience of qualitative research methods. 

To Apply: 

Please send a CV and covering letter expressing your interest to Prof Ann Blandford (A.Blandford@ucl.ac.uk) by 31st March 2020. Informal enquiries can also be made to Ann Blandford.