This paper is in the following e-collection/theme issue:

Focus Groups and Qualitative Research for Human Factors Research (1220) Artificial Intelligence (2129) Decision Support for Health Professionals (1539) Computer-Aided Diagnosis (251)

Published on in Vol 10 (2023)

This is a member publication of Glasgow Caledonian University (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40887, first published .
Optometrists' Perspectives Regarding Artificial Intelligence Aids and Contributing Retinal Images to a Repository: Web-Based Interview Study

Optometrists' Perspectives Regarding Artificial Intelligence Aids and Contributing Retinal Images to a Repository: Web-Based Interview Study

Optometrists' Perspectives Regarding Artificial Intelligence Aids and Contributing Retinal Images to a Repository: Web-Based Interview Study

Authors of this article:

Aurora Constantin1 Author Orcid Image ;   Malcolm Atkinson1 Author Orcid Image ;   Miguel Oscar Bernabeu2 Author Orcid Image ;   Fiona Buckmaster3 Author Orcid Image ;   Baljean Dhillon3 Author Orcid Image ;   Alice McTrusty3 Author Orcid Image ;   Niall Strang4 Author Orcid Image ;   Robin Williams5 Author Orcid Image
Article Authors Cited by (7) Tweetations (3) Metrics

Journals

  1. Schuitmaker L, Drogt J, Benders M, Jongsma K. Physicians’ required competencies in AI-assisted clinical settings: a systematic review. British Medical Bulletin 2025;153(1) View
  2. Saad A, Turgut F, Becker M, DeBuc D, Somfai G. Stakeholder Attitudes on AI Integration in Ophthalmology. Klinische Monatsblätter für Augenheilkunde 2025;242(04):515 View
  3. Tochel C, Bernabeu M, McTrusty A, Tatham A, Pead E, Buckmaster F, Penny J, MacGillivray T, Javidi M, Anderson H, Rubio A, Wallace R, Kidd J, MacLeod R, Strang N, Dhillon B. SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction. BMJ Health & Care Informatics 2025;32(1):e101236 View
  4. Ran A, Lui C, Tham Y, Cheng C, Lam C, Cheung W, Chan S, Ma H, Chow R, Yang D, Tang Z, Liu T, Tham C, Cheung C. The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis. Eye 2025;39(12):2353 View
  5. Ly A, Herse S, Williams M, Stapleton F. Artificial intelligence for age‐related macular degeneration diagnosis in Australia: A Novel Qualitative Interview Study. Ophthalmic and Physiological Optics 2025;45(6):1282 View
  6. Derksen C, Walter F, Akbar A, Parmar A, Saunders T, Round T, Rubin G, Scott S. The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: systematic review and recommendations. Implementation Science 2025;20(1) View
  7. Schaffernak I, Cecil J, Kleine A, Lermer E. Sociotechnical influences on the adoption and use of AI-enabled clinical decision support systems in ophthalmology: a theory-based interview study. BMC Health Services Research 2025;25(1) View