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Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology

Authors :
Lucy V. Cobbs
Hytham Al-Hindi
Cherie Fathy
Raziyeh Mahmoudzadeh
Tara Uhler
David Xu
Source :
Journal of Academic Ophthalmology, Vol 15, Iss 01, Pp e93-e98 (2023)
Publication Year :
2023
Publisher :
Thieme Medical Publishers, Inc., 2023.

Abstract

Purpose Ophthalmology residency training heavily relies on visual and pattern recognition-based learning. In parallel with traditional reference texts, online internet search via Google Image Search (GIS) is commonly used and offers an accessible fund of reference images for ophthalmology trainees seeking rapid exposure to images of retinal pathology. However, the accuracy and quality of this tool within this context is unknown. We aim to evaluate the accuracy and quality of GIS images of selected retinal pathologies. Methods A cross-sectional study was performed of GIS of 15 common and 15 rare retinal diseases drawn from the American Academy of Ophthalmology residency textbook series. A total of 300 evaluable image results were assessed for accuracy of images and image source accountability in consultation with a vitreoretinal surgeon. Results A total of 377 images were reviewed with 77 excluded prior to final analysis. A total of 288 (96%) search results accurately portrayed the retinal disease being searched, whereas 12 (4%) were of an erroneous diagnosis. More images of common retinal diseases were from patient education Web sites than were images of rare diseases (p

Details

Language :
English
ISSN :
24754757
Volume :
15
Issue :
01
Database :
Directory of Open Access Journals
Journal :
Journal of Academic Ophthalmology
Publication Type :
Academic Journal
Accession number :
edsdoj.8636000b32ef453783514046405d4a11
Document Type :
article
Full Text :
https://doi.org/10.1055/s-0043-1768025