Journal article
Deep learning: applications in retinal and optic nerve diseases
Clinical and Experimental Optometry, Vol.106(5), pp.466-475
2023
PMID: 35999058
Abstract
Deep learning (DL) represents a paradigm-shifting, burgeoning field of research with emerging clinical applications in optometry. Unlike traditional programming, which relies on human-set specific rules, DL works by exposing the algorithm to a large amount of annotated data and allowing the software to develop its own set of rules (i.e. learn) by adjusting the parameters inside the model (network) during a training process in order to complete the task on its own. One major limitation of traditional programming is that, with complex tasks, it may require an extensive set of rules to accurately complete the assignment. Additionally, traditional programming can be susceptible to human bias from programmer experience. With the dramatic increase in the amount and the complexity of clinical data, DL has been utilised to automate data analysis and thus to assist clinicians in patient management. This review will present the latest advances in DL, for managing posterior eye diseases as well as DL-based solutions for patients with vision loss.
Details
- Title
- Deep learning: applications in retinal and optic nerve diseases
- Authors
- Jason Charng (Corresponding Author) - University of Western AustraliaKhyber Alam (Author) - University of Western AustraliaGavin Swartz (Author) - University of Western AustraliaJason Kugelman (Author) - Queensland University of TechnologyDavid Alonso-Caneiro (Author) - Queensland University of TechnologyDavid A Mackey (Author) - University of Western AustraliaFred K Chen (Author) - University of Western Australia
- Publication details
- Clinical and Experimental Optometry, Vol.106(5), pp.466-475
- Publisher
- Taylor & Francis
- DOI
- 10.1080/08164622.2022.2111201
- ISSN
- 1444-0938
- PMID
- 35999058
- Grant note
- DAM is supported by a National Health and Medical Research Council practitioner fellowship [GNT1154518]. FKC receives funding from the National Health and Medical Research Council [Centre of Research Excellence Grant GNT1116360 and Fellowship MRF1142962]. DA-C receives funding from the National Health and Medical Research Council [Ideas Grant NHMRC 1186915].
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99973596102621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Ophthalmology
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Source: InCites