Using Artificial Intelligence to improve the diagnostic predictions of corneal topography machines for Keratoconus subjects

Research Opportunity
PhD students, Honours students
Number of Honour Places Available
1
Department / Centre
Surgery
Location
Surgery, Ophthalmology, Royal Victorian Eye and Ear Hospital
Primary Supervisor Email Number Webpage
Dr Srujana Sahebjada srujana.sahebjada@unimelb.edu.au
Co-supervisor Email Number Webpage
A/Prof Mark Daniel
Prof Paul Baird

Summary Keratoconus is a common condition that affects the cornea and despite its increasing prevalence, the cause of keratoconus is largely unknown. There are many clinical gaps regarding keratoconus in terms of subclinical detection, clarifying its disease stage and identifying which features should be used to predict its progression. These gaps impact on a clinician’s decision-making process for keratoconus disease management.

Project Details

Keratoconus is a common condition that affects the cornea and despite its increasing prevalence, the cause of keratoconus is largely unknown. There are many clinical gaps regarding keratoconus in terms of subclinical detection, clarifying its disease stage and identifying which features should be used to predict its progression. These gaps impact on a clinician’s decision-making process for keratoconus disease management. The project aims at developing machine learning algorithms to identify features that define early subclinical keratoconus that are currently refractory as well as identify a series of features that are involved in a) disease staging, as well as b) risk of progression of Keratoconus. It provides an exciting opportunity to conduct big data analysis, generate AI model and manuscript writing.

Students with backgrounds in biomedical and computer science, statistics or optometry and visual science are welcome to apply.


School Research Themes

Ageing



Research Opportunities

PhD students, Honours students
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research

Graduate Research application

Honours application

Key Contact

For further information about this research, please contact a supervisor.

Department / Centre

Surgery

Research Node

Surgery, Ophthalmology, Royal Victorian Eye and Ear Hospital

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