Ophthalmology

Automated feature selection for early keratoconus screening optimization.

In this paper, an automated feature selection (FS) method is presented to optimize machine learning ...

Quantifying interpretation reproducibility in Vision Transformer models with TAVAC.

Deep learning algorithms can extract meaningful diagnostic features from biomedical images, promisin...

Deep learning-based intratumoral and peritumoral features for differentiating ocular adnexal lymphoma and idiopathic orbital inflammation.

OBJECTIVES: To evaluate the value of deep-learning-based intratumoral and peritumoral features for d...

Exploring transparency: A comparative analysis of explainable artificial intelligence techniques in retinography images to support the diagnosis of glaucoma.

Machine learning models are widely applied across diverse fields, including nearly all segments of h...

Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis.

Inability to express the confidence level and detect unseen disease classes limits the clinical impl...

Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme.

AIMS: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retino...

Evaluation of prediction errors in nine intraocular lens calculation formulas using an explainable machine learning model.

BACKGROUND: The purpose of the study was to evaluate the relationship between prediction errors (PEs...

Machine and deep learning algorithms for sentiment analysis during COVID-19: A vision to create fake news resistant society.

Informal education via social media plays a crucial role in modern learning, offering self-directed ...

Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy.

Diabetic Retinopathy (DR) stands as a significant global cause of vision impairment, underscoring th...

Annotated interictal discharges in intracranial EEG sleep data and related machine learning detection scheme.

Interictal epileptiform discharges (IEDs) such as spikes and sharp waves represent pathological elec...

Editorial: The diagnoses of glaucoma in the era of artificial intelligence.

Benchmarking the performance of large language models in uveitis: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, Google Gemini, and Anthropic Claude3.

BACKGROUND/OBJECTIVE: This study aimed to evaluate the accuracy, comprehensiveness, and readability ...

Editorial: Efficient artificial intelligence (AI) in ophthalmic imaging.

Artificial intelligence-assisted fitting method using corneal topography outcomes enhances success rate in orthokeratology lens fitting.

PURPOSE: Based on ideal outcomes of corneal topography following orthokeratology (OK), an innovative...

L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction.

Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext...

Artificial intelligence and glaucoma: a lucid and comprehensive review.

Glaucoma is a pathologically irreversible eye illness in the realm of ophthalmic diseases. Because i...

Serum PD-1 regulation and PD-1 expression of CD4+Foxp3+ regulatory T cells in patients in thyroid eye disease associated with immunosuppression treatment.

PURPOSE: Thyroid eye disease (TED) primarily occurs in hyperthyroid patients, sometimes resulting in...

Exploring hyperspectral anomaly detection with human vision: A small target aware detector.

Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ f...

Attention and dilated convolutions inclusive deep-CNN with multiplexed texture features to diagnose Pathological and High Myopia.

In today's era, precise and timely diagnosis of ocular diseases are crucial as these disorders jeopa...

Advanced vision transformers and open-set learning for robust mosquito classification: A novel approach to entomological studies.

Mosquito-related diseases pose a significant threat to global public health, necessitating efficient...

Glaucoma detection: Binocular approach and clinical data in machine learning.

In this work, we present a multi-modal machine learning method to automate early glaucoma diagnosis....