The Centre for Eye Health has two new PhD positions now available to work with top scientists at the cutting-edge of clinical research. Research at CFEH is led by Centre Director Professor Michael Kalloniatis, and is affiliated with UNSW Sydney, one of Australia’s top universities.
The two positions relate to a project aimed at developing AI capabilities to improve optometry accuracy for patient diagnoses and referrals and is supported by CRC-P funding. The projects both have a clinical, diagnostic focus.
All PhD positions are contingent on a candidate’s ability to secure a competitive scholarship through the Domestic Research Training Program (RTP) or similar (28k per annum). A top-up component up to the value of an additional 75% of the full RTP stipend is also available for eligible candidates.
The full project descriptions are as follows:
Project title: The efficacy and implementation of primary care clinical decision support tools in retinal disease
Description: Misdiagnosis is common in optometry and leads to poor patient outcomes and unproductivity due to inappropriate specialist referrals. Clinical decision support systems describe information systems designed to improve diagnosis and referral decisions. Data from individual cases are conventionally analysed with or without the aid of artificial intelligence (AI) against a knowledge base using structured record keeping, knowledge reference systems, alert/reminder systems, diagnostic assistance and clinical data interpretation tools. Although clinical decision support technologies have a proven capacity to provide clinicians with timely, patient-specific recommendations for better individualised patient care, and better population health, the value of these technologies in a clinical setting requires validation. Practitioner readiness to embrace these technologies is also poorly understood.
This project will investigate the implementation and value of providing optometrists with various primary point-of-care clinical decision support strategies in retinal disease, including AI driven diagnostic and referral analytics and decision support.
Project title: Towards a unified glaucoma definition in clinical practice
Description: Glaucoma is the leading cause of irreversible blindness worldwide and presents a significant public health problem due to its chronic nature and frequency of underdiagnosis in the developed world. Despite a slew of available imaging and perimetric technologies available for assessing patients with suspected or manifest glaucoma, it remains clear that disease diagnosis still requires a Bayesian approach by the clinician. As such, there is a lack of clear understanding with regard to the significance of the contribution of individual clinical parameters, their fidelity and clinical utilisation that impairs the ability to arrive at a unified model for glaucoma diagnosis. This project aims develop potential problems to these enduring issues by examining barriers to the definition of glaucoma at the patient-, instrument- and clinician-related levels, supplemented by the contribution of technique-agnostic artificial intelligence models.
For further information on the awarded CRC-P Grant, please see here: