Team leader
The Data Analytics group is focused on discovering new knowledge by utilising the large amounts of data collected through both clinical and research activities at the Lions Eye Institute, and by combining clinical expertise with smart algorithm development. One characterisation of the activities of the group is into projects that affect local, statewide and global eye healthcare.
Locally, we are analysing clinical data within the Lions Eye Institute to assist our clinicians to maintain their best-practice activities and to aid constant reflection on our performance as a world leading eye healthcare facility. This information is also being used to construct and test new ways of interacting with the multiple sources of data that clinicians must make their judgements based upon, particularly in glaucoma.
Statewide, the emphasis is on communication between ophthalmology and optometry in both remote and metropolitan practices. We are building and testing methods that support collaboration between all eye healthcare practitioners in the state.
These local and statewide activities form the backbone for our contribution to the global research community. We maintain several open source software tools that are used by over 40 sites around the globe in research projects related to vision testing. Our fundamental investigations into algorithms for visual field testing have been adopted by several manufacturers worldwide, and we are the internationally recognised leaders in visual testing research for ophthalmology and optometry. We are working in close collaboration with several medical device manufacturers to develop new software that would further improve their devices.
It may seem strange that the above descriptions do not mention artificial intelligence (AI) as an Integral part of our work. Naturally we closely follow modern AI techniques and their potential in eye healthcare, adopting them when appropriate. Current AI methods are based on learning from existing data and, by definition, data can only encode the past. Moreover, many AI techniques operate as a “black box” with little insight into how decisions are being reached or what features of the data are important to that decision. Our emphasis is on discovery of new knowledge for the future that makes sense to human clinicians and patients.
