Fabian Yii

Thesis title: Developing Artificial Intelligence Approaches to Predicting Myopia Progression and Pathologic Myopia

Background

Optometrist by training; vision scientist under training.

Qualifications

BSc (Hons) Optometry, Glasgow Caledonian University

Postgraduate teaching

Machine Learning Practical (INFR11132), School of Informatics: Demonstrator/ Tutor/ Marker

Text Remix (EFIE11004), Edinburgh Futures Institute: Postgraduate Teaching Assistant

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

Conference details

International Visual Field & Imaging Symposium 2022, Berkeley, California: "Power to the People: Estimating the Detectability of Change in Individual Patients’ Visual Field Series" (online oral presentation)

MICCAI Workshop on Ophthalmic Medical Image Analysis 2022, Singapore: "Rethinking Retinal Image Quality: Treating Quality Threshold as a Tunable Hyperparameter" (poster presentation)

Prof Mingguang He, Centre for Eye Research Australia, University of Melbourne, Australia

Prof Paul H Artes,  Eye & Vision Research Group, University of Plymouth, UK

Dr Wang Wei, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, China

Yii, Fabian, Dutt, Raman, MacGillivray, Tom, Dhillon, Baljean, Bernabeu, Miguel, Strang, Niall (2022) 'Rethinking Retinal Image Quality: Treating Quality Threshold as a Tunable Hyperparameter' In: Antony, Bhavna, Fu, Huazhu, Lee, Cecilia, MacGillivray, Tom, Xu, Yawn, Zheng, Yalin (eds) Ophthalmic Medical Image Analysis. OMIA 2022. Lecture Notes in Computer Science, vol 13576. Springer, Cham. https://doi.org/10.1007/978-3-031-16525-2_8