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Diagnostic Techniques, Ophthalmological

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Examination of alternative eGFR definitions on the performance of deep learning models for detection of chronic kidney disease from fundus photographs.

PloS one
Deep learning (DL) models have shown promise in detecting chronic kidney disease (CKD) from fundus photographs. However, previous studies have utilized a serum creatinine-only estimated glomerular rate (eGFR) equation to measure kidney function despi...

Evaluating the Diagnostic Accuracy and Management Recommendations of ChatGPT in Uveitis.

Ocular immunology and inflammation
INTRODUCTION: Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice...

Automatic detection and differential diagnosis of age-related macular degeneration from color fundus photographs using deep learning with hierarchical vision transformer.

Computers in biology and medicine
Age-related macular degeneration (AMD) is a leading cause of vision loss in the elderly, highlighting the need for early and accurate detection. In this study, we proposed DeepDrAMD, a hierarchical vision transformer-based deep learning model that in...

Chatbots Vs. Human Experts: Evaluating Diagnostic Performance of Chatbots in Uveitis and the Perspectives on AI Adoption in Ophthalmology.

Ocular immunology and inflammation
PURPOSE: To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practic...

Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era.

Medical & biological engineering & computing
Recently, fundus photography (FP) is being increasingly used. Corneal curvature is an essential factor in refractive errors and is associated with several pathological corneal conditions. As FP-based examination systems have already been widely distr...

Artificial intelligence for glaucoma: state of the art and future perspectives.

Current opinion in ophthalmology
PURPOSE OF REVIEW: To address the current role of artificial intelligence (AI) in the field of glaucoma.

Diagnostic accuracy of artificial intelligence in detecting retinitis pigmentosa: A systematic review and meta-analysis.

Survey of ophthalmology
Retinitis pigmentosa (RP) is often undetected in its early stages. Artificial intelligence (AI) has emerged as a promising tool in medical diagnostics. Therefore, we conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy ...

Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography.

BMC medical informatics and decision making
BACKGROUND: The epiretinal membrane (ERM) is a common retinal disorder characterized by abnormal fibrocellular tissue at the vitreomacular interface. Most patients with ERM are asymptomatic at early stages. Therefore, screening for ERM will become in...

AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge.

IEEE transactions on medical imaging
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible. While AI models f...

Privacy-Preserving Federated Learning With Domain Adaptation for Multi-Disease Ocular Disease Recognition.

IEEE journal of biomedical and health informatics
As one of the effective ways of ocular disease recognition, early fundus screening can help patients avoid unrecoverable blindness. Although deep learning is powerful for image-based ocular disease recognition, the performance mainly benefits from a ...