Application of machine learning in ophthalmic imaging modalities
Y Tong, W Lu, Y Yu, Y Shen - Eye and Vision, 2020 - Springer
In clinical ophthalmology, a variety of image-related diagnostic techniques have begun to
offer unprecedented insights into eye diseases based on morphological datasets with …
offer unprecedented insights into eye diseases based on morphological datasets with …
Artificial intelligence for the diagnosis of retinopathy of prematurity: a systematic review of current algorithms
A Ramanathan, SE Athikarisamy, GC Lam - Eye, 2023 - nature.com
Abstract Background/Objectives With the increasing survival of premature infants, there is an
increased demand to provide adequate retinopathy of prematurity (ROP) services. Wide field …
increased demand to provide adequate retinopathy of prematurity (ROP) services. Wide field …
Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity
Background Prior work has demonstrated the near-perfect accuracy of a deep learning
retinal image analysis system for diagnosing plus disease in retinopathy of prematurity …
retinal image analysis system for diagnosing plus disease in retinopathy of prematurity …
External validation of a retinopathy of prematurity screening model using artificial intelligence in 3 low-and middle-income populations
Importance Retinopathy of prematurity (ROP) is a leading cause of preventable blindness
that disproportionately affects children born in low-and middle-income countries (LMICs). In …
that disproportionately affects children born in low-and middle-income countries (LMICs). In …
Federated learning for diagnosis of age-related macular degeneration
This paper presents a federated learning (FL) approach to train deep learning models for
classifying age-related macular degeneration (AMD) using optical coherence tomography …
classifying age-related macular degeneration (AMD) using optical coherence tomography …
Cost-effectiveness of artificial intelligence–based retinopathy of prematurity screening
SL Morrison, D Dukhovny, RVP Chan… - JAMA …, 2022 - jamanetwork.com
Importance Artificial intelligence (AI)–based retinopathy of prematurity (ROP) screening may
improve ROP care, but its cost-effectiveness is unknown. Objective To evaluate the relative …
improve ROP care, but its cost-effectiveness is unknown. Objective To evaluate the relative …
Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks
Purpose Accurate image-based ophthalmic diagnosis relies on fundus image clarity. This
has important implications for the quality of ophthalmic diagnoses and for emerging methods …
has important implications for the quality of ophthalmic diagnoses and for emerging methods …
Assessment of patient specific information in the wild on fundus photography and optical coherence tomography
In this paper we analyse the performance of machine learning methods in predicting patient
information such as age or sex solely from retinal imaging modalities in a heterogeneous …
information such as age or sex solely from retinal imaging modalities in a heterogeneous …
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
Diabetic retinopathy (DR) is a major cause of vision impairment in diabetic patients
worldwide. Due to its prevalence, early clinical diagnosis is essential to improve treatment …
worldwide. Due to its prevalence, early clinical diagnosis is essential to improve treatment …
Deep learning from “passive feeding” to “selective eating” of real-world data
Artificial intelligence (AI) based on deep learning has shown excellent diagnostic
performance in detecting various diseases with good-quality clinical images. Recently, AI …
performance in detecting various diseases with good-quality clinical images. Recently, AI …