James C Porter
Thesis title: Realising the potential of retinal image analysis with AI methods for monitoring neurodegenerative brain health in the community
Precision Medicine
Year of study: 2
- Centre for Medical Informatics, Usher Institute
- Scottish Collaborative Optometry-Ophthalmology Network e-research (SCONe)
- Precision Medicine, Deanery of Molecular, Genetic and Population Health Sciences
Contact details
- Email: james.porter@ed.ac.uk
PhD supervisors:
Address
- Street
-
Usher Building,
The University of Edinburgh
5‒7 Little France Road,
Edinburgh BioQuarter ‒ Gate 3 - City
- Edinburgh
- Post code
- EH16 4UX
Background
I am a computer scientist by background, where I have focused on machine learning at scale. Recently, I have pivoted to machine learning applied to retinal images for neurodegenerative disease prediction.
Qualifications
MSc Artificial Intelligence, The University of Edinburgh (2021)
BSc Computer Science, Keele University (2017)
Responsibilities & affiliations
Centre for Medical Informatics (CMI), Usher Institute Scottish Collaborative Optometry-Ophthalmology Network e-research (SCONe)
Open to PhD supervision enquiries?
No
Research summary
Applying machine learning techniques to improve medical diagnosis.
Current research interests
Fundus & OCT images of the retina. Neurodegenerative disease. Small Vessel Disease.Past research interests
Extreme classification. Behaviour prediction. Memory efficient classification. Exploratory data analysis.Knowledge exchange
UK Biobank, SCONe.
Affiliated research centres
Project activity
UK Biobank neurodegenerative disease prediction from fundus images.
Conference details
2025 ARVO Imaging in the Eye - Salt Lake City, USA.
Papers delivered
Prediction of Optical Coherence Tomography Retinal Layer Thickness from Colour Fundus Photography in the UK Biobank. Porter, J. C., Bernabeu, M. O. & Dhillon, B., 3 May 2025, In: Investigative Ophthalmology & Visual Science (IOVS).