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Ophthalmology Science is a peer-reviewed journal published by Elsevier, covering Retinal Diseases and Treatments, Ophthalmology and Visual Impairment Studies, Retinal Imaging and Analysis.
| Publisher | Elsevier |
|---|---|
| Reference style | Numbered (Elsevier) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, C. Lee, A representative article title, Ophthalmology Science 12 (2023) 45–58.
Formats any DOI in Ophthalmology Science style. No sign-up. |
| Publishes research in | Retinal Diseases and Treatments Ophthalmology and Visual Impairment Studies Retinal Imaging and Analysis Glaucoma and retinal disorders Corneal surgery and disorders |
| ISSN | 2666-9145 |
| Citation impact (2-yr) | 2.87 |
| h-index | 37 |
| i10-index | 316 |
| Total citations | 9,136 |
| Article processing charge | $2,500 |
| Open access | Yes |
| Top institutions publishing here | Harvard University |
| Journal website | www.journals.elsevier.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
PurposeFoundation models are a novel type of artificial intelligence algorithms, in which models are pretrained at scale on unannotated data and fine-tuned for a myriad of downstream tasks, such as generating text. This study assessed the accuracy of ChatGPT, a large language model (LLM), in the ophthalmology question-answering space.DesignEvaluation of diagnostic test or technology.ParticipantsChatGPT is…
ObjectiveTo compare general ophthalmologists, retina specialists, and the EyeArt Artificial Intelligence (AI) system to the clinical reference standard for detecting more than mild diabetic retinopathy (mtmDR).DesignProspective, pivotal, multicenter trial conducted from April 2017 to May 2018.ParticipantsParticipants were aged ≥ 18 years who had diabetes mellitus and underwent dilated ophthalmoscopy. A total of 521 of 893…
Purpose: To compare the diagnostic accuracy and explainability of a Vision Transformer deep learning technique, Data-efficient image Transformer (DeiT), and ResNet-50, trained on fundus photographs from the Ocular Hypertension Treatment Study (OHTS) to detect primary open-angle glaucoma (POAG) and identify the salient areas of the photographs most important for each model's decision-making process. Design: Evaluation…
The rapid progress of large language models (LLMs) driving generative artificial intelligence applications heralds the potential of opportunities in health care. We conducted a review up to April 2023 on Google Scholar, Embase, MEDLINE, and Scopus using the following terms: "large language models," "generative artificial intelligence," "ophthalmology," "ChatGPT," and "eye," based on relevance to this…
Purpose: To evaluate the performance of a federated learning framework for deep neural network-based retinal microvasculature segmentation and referable diabetic retinopathy (RDR) classification using OCT and OCT angiography (OCTA). Design: Retrospective analysis of clinical OCT and OCTA scans of control participants and patients with diabetes. Participants: The 153 OCTA en face images used for microvasculature…
