My research is centred on using data to better understand the most common causes of vision loss.

Developing Machine Learning pipelines for ophthalmic data

A major strand of my work is a deeper exploration of ophthalmic data from the Northern Ireland Cohort for the Longitudinal study of Ageing (NICOLA) using cutting-edge data science techniques. I am interested in the use of ensemble models to flexibly model tabular data and interpretable Machine Learning techniques to separate signal from noise.

Large scale analysis of Electronic Medical Records

I am analysing two large datasets of anonymised electronic medical records.

The first is a study into the use of machine learning to identify factors associated with long term response to wet AMD treatment, using records of ~4500 patients over a 12 year period.

The second is a multi-centre health technology assessment funded by the National Institute for Health Research, using records from ~13,000 patients to predict risk of conversion from ocular hypertension to glaucoma.

Undergraduate

Module Co-ordinator and Lecturer - "The rise of Artificial Intelligence in healthcare" (3rd Year Medicine)

Personal tutor and Portfolio adviser to 12 undergraduate Medical students

Statistics practical classes (Bio-Medical Sciences)

Postgraduate

R programming (Bioinformatics, Research Skills in Experimental Medicine)

Statistics practical classes (Medical Statistics)

PhD Supervision

Hannah Griffin (2nd Supervisor)

MD Supervision

John Smith (3rd Supervisor)