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 …
Applications of deep learning in fundus images: A review
The use of fundus images for the early screening of eye diseases is of great clinical
importance. Due to its powerful performance, deep learning is becoming more and more …
importance. Due to its powerful performance, deep learning is becoming more and more …
A deep learning system for predicting time to progression of diabetic retinopathy
Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk
of DR progression is highly variable among different individuals, making it difficult to predict …
of DR progression is highly variable among different individuals, making it difficult to predict …
Artificial intelligence and deep learning in ophthalmology
Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global
interest in recent years. DL has been widely adopted in image recognition, speech …
interest in recent years. DL has been widely adopted in image recognition, speech …
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) …
An overview of artificial intelligence in diabetic retinopathy and other ocular diseases
Artificial intelligence (AI), also known as machine intelligence, is a branch of science that
empowers machines using human intelligence. AI refers to the technology of rendering …
empowers machines using human intelligence. AI refers to the technology of rendering …
Benchmarking saliency methods for chest X-ray interpretation
Saliency methods, which produce heat maps that highlight the areas of the medical image
that influence model prediction, are often presented to clinicians as an aid in diagnostic …
that influence model prediction, are often presented to clinicians as an aid in diagnostic …
[HTML][HTML] Trustworthy AI: closing the gap between development and integration of AI systems in ophthalmic practice
C González-Gonzalo, EF Thee, CCW Klaver… - Progress in retinal and …, 2022 - Elsevier
An increasing number of artificial intelligence (AI) systems are being proposed in
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …
Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective …
Background By 2050, almost 5 billion people globally are projected to have myopia, of
whom 20% are likely to have high myopia with clinically significant risk of sight-threatening …
whom 20% are likely to have high myopia with clinically significant risk of sight-threatening …
Detection of anaemia from retinal fundus images via deep learning
A Mitani, A Huang, S Venugopalan… - Nature biomedical …, 2020 - nature.com
Owing to the invasiveness of diagnostic tests for anaemia and the costs associated with
screening for it, the condition is often undetected. Here, we show that anaemia can be …
screening for it, the condition is often undetected. Here, we show that anaemia can be …