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Diagnosing glaucoma in primary eye care and the role of Artificial Intelligence applications for reducing the prevalence of undetected glaucoma in Australia.
Jan, Catherine; He, Mingguang; Vingrys, Algis; Zhu, Zhuoting; Stafford, Randall S.
Afiliación
  • Jan C; Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia. cjan541@gmail.com.
  • He M; Ophthalmology, Department of Surgery, Faculty of Medicine, Dentistry & Health Sciences, University of Melbourne, Melbourne, VIC, Australia. cjan541@gmail.com.
  • Vingrys A; Lost Child's Vision Project, Sydney, NSW, Australia. cjan541@gmail.com.
  • Zhu Z; Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia.
  • Stafford RS; Ophthalmology, Department of Surgery, Faculty of Medicine, Dentistry & Health Sciences, University of Melbourne, Melbourne, VIC, Australia.
Eye (Lond) ; 38(11): 2003-2013, 2024 Aug.
Article en En | MEDLINE | ID: mdl-38514852
ABSTRACT
Glaucoma is the commonest cause of irreversible blindness worldwide, with over 70% of people affected remaining undiagnosed. Early detection is crucial for halting progressive visual impairment in glaucoma patients, as there is no cure available. This narrative review aims to identify reasons for the significant under-diagnosis of glaucoma globally, particularly in Australia, elucidate the role of primary healthcare in glaucoma diagnosis using Australian healthcare as an example, and discuss how recent advances in artificial intelligence (AI) can be implemented to improve diagnostic outcomes. Glaucoma is a prevalent disease in ageing populations and can have improved visual outcomes through appropriate treatment, making it essential for general medical practice. In countries such as Australia, New Zealand, Canada, USA, and the UK, optometrists serve as the gatekeepers for primary eye care, and glaucoma detection often falls on their shoulders. However, there is significant variation in the capacity for glaucoma diagnosis among eye professionals. Automation with Artificial Intelligence (AI) analysis of optic nerve photos can help optometrists identify high-risk changes and mitigate the challenges of image interpretation rapidly and consistently. Despite its potential, there are significant barriers and challenges to address before AI can be deployed in primary healthcare settings, including external validation, high quality real-world implementation, protection of privacy and cybersecurity, and medico-legal implications. Overall, the incorporation of AI technology in primary healthcare has the potential to reduce the global prevalence of undiagnosed glaucoma cases by improving diagnostic accuracy and efficiency.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Atención Primaria de Salud / Inteligencia Artificial / Glaucoma Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Eye (Lond) / Eye (Lond. 1987) / Eye (London. 1987) Asunto de la revista: OFTALMOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Atención Primaria de Salud / Inteligencia Artificial / Glaucoma Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Eye (Lond) / Eye (Lond. 1987) / Eye (London. 1987) Asunto de la revista: OFTALMOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Australia