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

E3S Web of Conferences Pub Date : 2023-04-12 eCollection Date: 2023-01-01 DOI:10.1055/s-0043-1768025
Lucy V Cobbs, Hytham Al-Hindi, Cherie Fathy, Raziyeh Mahmoudzadeh, Tara Uhler, David Xu
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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  < 0.01). Significantly more images of rare retinal diseases were found in peer-reviewed sources ( p  = 0.01). Conclusions  GIS search results yielded a modest level of accuracy for the purposes of ophthalmic education. Despite the ease and rapidity of accessing multimodal retinal imaging examples, this tool may best be suited as a supplementary resource for learning among residents due to limited accuracy, lack of sufficient supporting information, and the source Web site's focus on patient education.

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将互联网图像搜索作为视网膜病理学学习工具的准确性和实用性。
目的 眼科住院医师培训在很大程度上依赖于以视觉和模式识别为基础的学习。在使用传统参考文献的同时,通过谷歌图像搜索(GIS)进行的在线互联网搜索也被广泛使用,这为寻求快速接触视网膜病理学图像的眼科受训人员提供了可获取的参考图像资源。然而,这一工具在这方面的准确性和质量尚不清楚。我们旨在评估选定视网膜病变 GIS 图像的准确性和质量。方法 我们对美国眼科学会住院医师系列教材中 15 种常见和 15 种罕见视网膜疾病的 GIS 进行了横断面研究。在咨询玻璃体视网膜外科医生后,对总共 300 张可评估的图像结果进行了评估,以确定图像的准确性和图像来源的可靠性。结果 共审查了 377 幅图像,其中 77 幅在最终分析前被排除。共有 288 张(96%)搜索结果准确描述了所搜索的视网膜疾病,而 12 张(4%)诊断有误。来自患者教育网站的常见视网膜疾病图片多于罕见疾病图片(P P = 0.01)。结论 GIS 搜索结果在眼科教育方面具有一定的准确性。尽管获取多模态视网膜成像示例既方便又快捷,但由于准确性有限、缺乏足够的支持信息以及源网站侧重于患者教育,该工具可能最适合作为住院医师学习的补充资源。
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来源期刊
E3S Web of Conferences
E3S Web of Conferences Energy-Energy (all)
CiteScore
0.90
自引率
0.00%
发文量
1133
期刊介绍: E3S Web of Conferences is an Open Access publication series dedicated to archiving conference proceedings in all areas related to Environment, Energy and Earth Sciences. The journal covers the technological and scientific aspects as well as social and economic matters. Major disciplines include: soil sciences, hydrology, oceanography, climatology, geology, geography, energy engineering (production, distribution and storage), renewable energy, sustainable development, natural resources management… E3S Web of Conferences offers a wide range of services from the organization of the submission of conference proceedings to the worldwide dissemination of the conference papers. It provides an efficient archiving solution, ensuring maximum exposure and wide indexing of scientific conference proceedings. Proceedings are published under the scientific responsibility of the conference editors.
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