Latest AI and machine learning research in glaucoma for healthcare professionals.
BACKGROUND AND OBJECTIVE: This paper builds different neural network models with simple topologies, having one or two hidden layers which were subsequently employed in the prediction of ocular changes progression in patients with diabetes associated with primer open-angle glaucoma.
Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using...
This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default setting...
The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal n...
Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in ...
PURPOSE: To investigate the safety and synergistic effect of topical bevacizumab after trabeculectomy surgery with mitomycin C (MMC).
We present a novel method to segment retinal images using ensemble learning based convolutional neural network (CNN) architectures. An entropy samplin...
This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vis...
OBJECTIVE: To determine the progression of pigment dispersion syndrome (PDS) into pigmentary glaucoma (PG) in a population at the Central Military Hos...
Classification of different mechanisms of angle closure glaucoma (ACG) is important for medical diagnosis. Error-correcting output code (ECOC) is an e...
Glaucoma is among the most common causes of permanent blindness in human. Because the initial symptoms are not evident, mass screening would assist ea...
BACKGROUND: Robot-assisted laparoscopic radical prostatectomy (RALP) is a minimally invasive surgical procedure for prostate cancer. During RALP, the ...
Frozen encoders are chosen by how well a lightweight head reads a finding from their features, not whether the geometry separates it. Nearest-neighbor...
Background: Retinal fundus imaging is central to the early diagnosis of sight-threatening conditions including diabetic retinopathy, glaucoma, and ret...
Scalable Bayesian inference for generalized linear mixed models (GLMMs) provides uncertainty-aware analysis of correlated longitudinal data, but exist...
Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer l...
Forecasting visual fields (VFs) is critical for personalized monitoring and treatment planning in glaucoma. This is inherently uncertain due to hetero...
Automated glaucoma subtype classification from clinical notes remains clinically unactionable without subspecialty-aligned explanations supporting cli...
Purpose: To determine whether disease-aware adversarial perturbations can reduce demographic recoverability encoded in color fundus photographs (CFPs)...
Purpose: To evaluate the performance of secure cloud-based large language models (LLMs) in extracting glaucoma diagnosis, type, and severity from free...