Comparing code-free and bespoke deep learning approaches in ophthalmology
Authors (first, second and last of 6)
Collection
Breakthroughs in Artificial Intelligence for Ophthalmology
This topical collection in Graefe's Archive for Clinical and Experimental Ophthalmology seeks to present articles that describe novel applications and significant advances in AI for ophthalmology. Articles that describe development and validation of new algorithms or neural networks for solving specific diagnostic or prognostic challenges in ophthalmology are of particular interest. Also of interest are articles that describe and evaluate the implementation or deployment of AI algorithms in clinical settings. Highly technical articles which are focused on computer engineering concepts are not well-suited for this collection.
Editors
-
Oliver Zeitz
Professor Zeitz is a retina specialist and board-certified ophthalmologist. As of October 2017, he was appointed as the Head of the Campus Benjamin Franklin site of the Charité Department of Ophthalmology in Berlin, Germany. In addition to his clinical duties, Professor Zeitz conducts research on retinal and macular diseases with the aim to provide better and more effective treatments to patients. Professor Zeitz has co-authored more than 80 scientific publications, and he is an Associate Editor of Graefe’s Archive for Clinical and Experimental Ophthalmology and the Journal of Ocular Pharmacology and Therapeutics.
Articles (32 in this collection)
-
-
Retinal imaging and Alzheimer’s disease: a future powered by Artificial Intelligence
Authors (first, second and last of 5)
-
Corneal biomechanics in early diagnosis of keratoconus using artificial intelligence
Authors (first, second and last of 4)
-
The effect of optical degradation from cataract using a new Deep Learning optical coherence tomography segmentation algorithm
Authors (first, second and last of 8)
-
Behind the mask: a critical perspective on the ethical, moral, and legal implications of AI in ophthalmology
Authors (first, second and last of 6)
-
A case study in applying artificial intelligence-based named entity recognition to develop an automated ophthalmic disease registry
Authors (first, second and last of 8)
-
A deep learning approach to investigate the filtration bleb functionality after glaucoma surgery: a preliminary study
Authors (first, second and last of 13)
-
Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review
Authors (first, second and last of 13)
-
-
An AI model to estimate visual acuity based solely on cross-sectional OCT imaging of various diseases
Authors (first, second and last of 7)
-
Artificial intelligence in retinal disease: clinical application, challenges, and future directions
Authors (first, second and last of 7)
-
Artificial intelligence-based ChatGPT chatbot responses for patient and parent questions on vernal keratoconjunctivitis
Authors (first, second and last of 4)
-
-
Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images
Authors (first, second and last of 6)
-
Artificial intelligence using deep learning to predict the anatomical outcome of rhegmatogenous retinal detachment surgery: a pilot study
Authors (first, second and last of 8)
-
Wide-field swept-source OCT angiography (23 × 20 mm) for detecting retinal neovascularization in eyes with proliferative diabetic retinopathy
Authors (first, second and last of 4)
-
Automated machine learning–based classification of proliferative and non-proliferative diabetic retinopathy using optical coherence tomography angiography vascular density maps
Authors (first, second and last of 14)
-
Emerging applications of bioinformatics and artificial intelligence in the analysis of biofluid markers involved in retinal occlusive diseases: a systematic review
Authors (first, second and last of 6)
-
-
Validation of an autonomous artificial intelligence–based diagnostic system for holistic maculopathy screening in a routine occupational health checkup context
Authors (first, second and last of 8)
-
Algorithm of the major and minor diagnostic criteria for active myopic choroidal neovascularization
Authors (first, second and last of 12)
-
Evaluating an automated machine learning model that predicts visual acuity outcomes in patients with neovascular age-related macular degeneration
Authors (first, second and last of 10)
-
End-to-end diabetic retinopathy grading based on fundus fluorescein angiography images using deep learning
Authors (first, second and last of 11)
-
Clinically applicable deep learning-based decision aids for treatment of neovascular AMD
Authors (first, second and last of 9)
-
Developing an iOS application that uses machine learning for the automated diagnosis of blepharoptosis
Authors (first, second and last of 8)
-
Prediction of postoperative visual acuity after vitrectomy for macular hole using deep learning–based artificial intelligence
Authors (first, second and last of 8)
-
Automated detection of severe diabetic retinopathy using deep learning method
Authors (first, second and last of 14)
-
Automatic detection of leakage point in central serous chorioretinopathy of fundus fluorescein angiography based on time sequence deep learning
Authors (first, second and last of 8)
-
Classification of pachychoroid on optical coherence tomography using deep learning
Authors (first, second and last of 6)
-
Development of a deep-learning system for detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus images: a pilot study
Authors (first, second and last of 8)
-
Sex judgment using color fundus parameters in elementary school students
Authors (first, second and last of 7)
-
