An overview of artificial intelligence in diabetic retinopathy and other ocular diseases

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers

(2022) Kaveri A. Thakoor et al.   Scientific Reports

Evaluation of machine learning algorithms for trabeculectomy outcome prediction in patients with glaucoma

(2022) Hasan Ul Banna et al.   Scientific Reports

A deep learning approach for detection of shallow anterior chamber depth based on the hidden features of fundus photographs

(2022) Tae Keun Yoo et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Prediction of treatment outcome in neovascular age-related macular degeneration using a novel convolutional neural network

(2022) Tsai-Chu Yeh et al.   Scientific Reports

Glaucoma diagnosis using multi-feature analysis and a deep learning technique

(2022) Nahida Akter et al.   Scientific Reports

Predicting the central 10 degrees visual field in glaucoma by applying a deep learning algorithm to optical coherence tomography images

(2021) Shotaro Asano et al.   Scientific Reports

A novel retinal ganglion cell quantification tool based on deep learning

(2021) Luca Masin et al.   Scientific Reports

Precise higher-order reflectivity and morphology models for early diagnosis of diabetic retinopathy using OCT images

(2021) A. Sharafeldeen et al.   Scientific Reports

Automated detection of glaucoma with interpretable machine learning using clinical data and multi-modal retinal images

(2021) Parmita Mehta et al.   AMERICAN JOURNAL OF OPHTHALMOLOGY

Understanding inherent image features in CNN-based assessment of diabetic retinopathy

(2021) Roc Reguant et al.   Scientific Reports

Deep learning-based automated detection for diabetic retinopathy and diabetic macular oedema in retinal fundus photographs

(2021) Feng Li et al.   EYE

Automated detection of retinal exudates and drusen in ultra-widefield fundus images based on deep learning

(2021) Zhongwen Li et al.   EYE

A deep learning system for detecting diabetic retinopathy across the disease spectrum

(2021) Ling Dai et al.   Nature Communications

Automated segmentation of macular edema for the diagnosis of ocular disease using deep learning method

(2021) Zhenhua Wang et al.   Scientific Reports

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images

(2021) Kang Zhang et al.   Nature Biomedical Engineering

Artificial intelligence-based detection of epimacular membrane from color fundus photographs

(2021) Enhua Shao et al.   Scientific Reports

Comparisons of deep learning algorithms for diagnosing bacterial keratitis via external eye photographs

(2021) Ming-Tse Kuo et al.   Scientific Reports

Estimation of current and post-treatment retinal function in chronic central serous chorioretinopathy using artificial intelligence

(2021) Maximilian Pfau et al.   Scientific Reports

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions

(2021) Mohammed Al-Mukhtar et al.   Scientific Reports

A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography

(2021) Gahyung Ryu et al.   Scientific Reports

A transcriptome-wide association study based on 27 tissues identifies 106 genes potentially relevant for disease pathology in age-related macular degeneration

(2020) Tobias Strunz et al.   Scientific Reports

Macular Ganglion Cell-Inner Plexiform Layer Thickness Prediction from Red-free Fundus Photography using Hybrid Deep Learning Model

(2020) Jinho Lee et al.   Scientific Reports

Predicting conversion to wet age-related macular degeneration using deep learning

(2020) Jason Yim et al.   NATURE MEDICINE

Prediction of age-related macular degeneration disease using a sequential deep learning approach on longitudinal SD-OCT imaging biomarkers

(2020) Imon Banerjee et al.   Scientific Reports

11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes—2021

(2020)   DIABETES CARE

Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data

(2020) Avyuk Dixit et al.   OPHTHALMOLOGY

Glaucoma diagnosis in the Chinese context: An uncertainty information-centric Bayesian deep learning model

(2020) Yidong Chai et al.   INFORMATION PROCESSING & MANAGEMENT

Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

(2019) Saleha Masood et al.   Scientific Reports

Ultrasound image analysis using deep learning algorithm for the diagnosis of thyroid nodules

(2019) Junho Song et al.   MEDICINE

Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading

(2019) Jaakko Sahlsten et al.   Scientific Reports

Computer-aided diagnosis of cataract using deep transfer learning

(2019) Turimerla Pratap et al.   Biomedical Signal Processing and Control

Universal artificial intelligence platform for collaborative management of cataracts

(2019) Xiaohang Wu et al.   BRITISH JOURNAL OF OPHTHALMOLOGY

Evaluating Glaucoma Treatment Effect on Intraocular Pressure Reduction Using Propensity Score Weighted Regression

(2019) Mengfei Wu et al.   Scientific Reports

Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder

(2019) Samuel I. Berchuck et al.   Scientific Reports

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

(2018) Daniel S. Kermany et al.   CELL

Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence

(2018) Ramachandran Rajalakshmi et al.   EYE

A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography

(2018) Felix Grassmann et al.   OPHTHALMOLOGY

Feasibility and patient acceptability of a novel artificial intelligence-based screening model for diabetic retinopathy at endocrinology outpatient services: a pilot study

(2018) Stuart Keel et al.   Scientific Reports

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

(2018) James M. Brown et al.   JAMA Ophthalmology

Development of a deep residual learning algorithm to screen for glaucoma from fundus photography

(2018) Naoto Shibata et al.   Scientific Reports

Fundus photograph-based deep learning algorithms in detecting diabetic retinopathy

(2018) Rajiv Raman et al.   EYE

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs

(2018) Mark Christopher et al.   Scientific Reports

Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network

(2018) Fei Li et al.   BMC MEDICAL IMAGING

Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning

(2017) Maximilian Treder et al.   GRAEFES ARCHIVE FOR CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY

Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes

(2017) Daniel Shu Wei Ting et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Unintended Consequences of Machine Learning in Medicine

(2017) Federico Cabitza et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network

(2017) Jianning Chi et al.   JOURNAL OF DIGITAL IMAGING

A computer-aided diagnostic system for detecting diabetic retinopathy in optical coherence tomography images

(2017) Ahmed ElTanboly et al.   MEDICAL PHYSICS

Automated Identification of Diabetic Retinopathy Using Deep Learning

(2017) Rishab Gargeya et al.   OPHTHALMOLOGY

Deep-learning based, automated segmentation of macular edema in optical coherence tomography

(2017) Cecilia S. Lee et al.   Biomedical Optics Express

Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images

(2017) Samina Khalid et al.   Biomed Research International

Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks

(2017) Philippe M. Burlina et al.   JAMA Ophthalmology

Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment

(2017) Hideharu Ohsugi et al.   Scientific Reports

Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

(2016) Arnaud Arindra Adiyoso Setio et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

(2016) Varun Gulshan et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Retinal optic disc localization using convergence tracking of blood vessels

(2016) Rui Wang et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Vessel extraction from non-fluorescein fundus images using orientation-aware detector

(2015) Benjun Yin et al.   MEDICAL IMAGE ANALYSIS

Deep learning

(2015) Yann LeCun et al.   NATURE

Age-Related Macular Degeneration

(2013) Lily K. Cheung et al.   PHARMACOTHERAPY

Global Prevalence and Major Risk Factors of Diabetic Retinopathy

(2012) J. W. Y. Yau et al.   DIABETES CARE