Fabian Yii

Thesis title: Developing Artificial Intelligence Approaches to Predicting Myopia Progression and Risk of Myopic Complications Based on Optometry Data

Background

I graduated from Glasgow Caledonian University with a BSc (Hons) Optometry in 2020.  I then spent a year in clinical practice back in Kuala Lumpur, dealing mainly with cataract and refractive surgery patients. During the same period, I was involved in a randomised controlled trial of a novel lens design (Defocus Incorporated Multiple Segments technology) for myopia control in my capacity as a research assistant at the National University of Malaysia. I also enjoyed a brief stint working with Professor Paul Artes (https://scholar.google.com/citations?user=Ew5C1fUAAAAJ&hl=en) on some research pertaining to visual field analysis before embarking on my PhD.

Qualifications

BSc (Hons) Optometry, Glasgow Caledonian University

Research summary

I'm currently working on developing artificial intelligence models to predict myopia progression and risk of pathologic myopia from retinal images, optical coherence tomography (OCT) scans and other relevant clinical features. The research will tap into the Scottish Collaborative Optometry-Ophthalmology Network e-research (SCONe) dataset, a large research repository of (primarily) retinal images curated from primary care optometry. 

Previously, I worked on assessing the ability of a visual field progression analysis called Permutation of Pointwise Linear Regression (PoPLR) in detecting various rates of visual field progression by means of Monte Carlo simulation in R.  The work was presented at a virtual Crabb Lab (http://www.staff.city.ac.uk/crabblab/#/) meeting.

My undergraduate honours project focused on the effect of bright light on choroidal thickness in young adults with low hyperopia or emmetropia.

Affiliated research centres