David Wright

Dr

  • Room 03.008 - Clinical Science A

    United Kingdom

Accepting PhD Students

PhD projects

Dr Wright is open to wide-ranging PhD applications from candidates with backgrounds in statistics, data science or computer science (including those with clinical experience). His areas of interest include: interpretable Machine Learning, integration of multi-modal data and federated analytics.

20092022

Research activity per year

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Personal profile

Research Statement

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.

Teaching

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)

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 10 - Reduced Inequalities
  • SDG 11 - Sustainable Cities and Communities

Network

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