Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective
The simultaneous maturation of multiple digital and telecommunications technologies in
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …
Deep learning in ophthalmology: the technical and clinical considerations
The advent of computer graphic processing units, improvement in mathematical models and
availability of big data has allowed artificial intelligence (AI) using machine learning (ML) …
availability of big data has allowed artificial intelligence (AI) using machine learning (ML) …
Performance of deep learning architectures and transfer learning for detecting glaucomatous optic neuropathy in fundus photographs
The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON)
in fundus photographs was evaluated. A large database of fundus photographs (n= 14,822) …
in fundus photographs was evaluated. A large database of fundus photographs (n= 14,822) …
DeepSeeNet: a deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs
Purpose In assessing the severity of age-related macular degeneration (AMD), the Age-
Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of …
Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of …
Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network
JH Lee, DH Kim, SN Jeong - Oral diseases, 2020 - Wiley Online Library
Objectives The aim of the current study was to evaluate the detection and diagnosis of three
types of odontogenic cystic lesions (OCLs)—odontogenic keratocysts, dentigerous cysts …
types of odontogenic cystic lesions (OCLs)—odontogenic keratocysts, dentigerous cysts …
Automatic glaucoma classification using color fundus images based on convolutional neural networks and transfer learning
JJ Gómez-Valverde, A Antón, G Fatti… - Biomedical optics …, 2019 - opg.optica.org
Glaucoma detection in color fundus images is a challenging task that requires expertise and
years of practice. In this study we exploited the application of different Convolutional Neural …
years of practice. In this study we exploited the application of different Convolutional Neural …
Optical coherence tomography and glaucoma
A Geevarghese, G Wollstein, H Ishikawa… - Annual review of …, 2021 - annualreviews.org
Early detection and monitoring are critical to the diagnosis and management of glaucoma, a
progressive optic neuropathy that causes irreversible blindness. Optical coherence …
progressive optic neuropathy that causes irreversible blindness. Optical coherence …
Detecting glaucoma with only OCT: Implications for the clinic, research, screening, and AI development
A method for detecting glaucoma based only on optical coherence tomography (OCT) is of
potential value for routine clinical decisions, for inclusion criteria for research studies and …
potential value for routine clinical decisions, for inclusion criteria for research studies and …
The current state of artificial intelligence in ophthalmology
R Kapoor, SP Walters, LA Al-Aswad - Survey of ophthalmology, 2019 - Elsevier
Artificial intelligence (AI) is a branch of computer science that deals with the development of
algorithms that seek to simulate human intelligence. We provide an overview of the basic …
algorithms that seek to simulate human intelligence. We provide an overview of the basic …
Deep learning in glaucoma with optical coherence tomography: a review
Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks,
has made significant breakthroughs in medical imaging, particularly for image classification …
has made significant breakthroughs in medical imaging, particularly for image classification …