Ophthalmology

Latest AI and machine learning research in ophthalmology for healthcare professionals.

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Dynamic blinking feature extraction for automated facial nerve paralysis detection.

Facial nerve paralysis (FNP) impair eyelid closure and blinking, risking ophthalmic complications an...

Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.

Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly impro...

Detection of Alzheimer Disease in Neuroimages Using Vision Transformers: Systematic Review and Meta-Analysis.

BACKGROUND: Alzheimer disease (AD) is a progressive condition characterized by cognitive decline and...

Enhanced crayfish optimization algorithm: Orthogonal refracted opposition-based learning for robotic arm trajectory planning.

In high-dimensional scenarios, trajectory planning is a challenging and computationally complex opti...

Cost-efficient training of hyperspectral deep learning models for the detection of contaminating grains in bulk oats by fluorescent tagging.

Computer vision based on instance segmentation deep learning models offers great potential for autom...

Computer-aided cholelithiasis diagnosis using explainable convolutional neural network.

Accurate and precise identification of cholelithiasis is essential for saving the lives of millions ...

Assessing the performance of Microsoft Copilot, GPT-4 and Google Gemini in ophthalmology.

OBJECTIVE: To evaluate the performance of large language models (LLMs), specifically Microsoft Copil...

Integrating Eye Tracking With Grouped Fusion Networks for Semantic Segmentation on Mammogram Images.

Medical image segmentation has seen great progress in recent years, largely due to the development o...

Rim learning framework based on TS-GAN: A new paradigm of automated glaucoma screening from fundus images.

Glaucoma detection from fundus images often relies on biomarkers such as the Cup-to-Disc Ratio (CDR)...

Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning.

In the wagyu industry worldwide, high-quality marbling beef is produced by promoting intramuscular f...

[Use of Artificial Intelligence in Diabetic Retinopathy Screening: Experience in a Health Service in Santiago, Chile].

UNLABELLED: Early detection of diabetic retinopathy is critical for preventing vision loss.

Efficient diagnosis of retinal disorders using dual-branch semi-supervised learning (DB-SSL): An enhanced multi-class classification approach.

The early diagnosis of retinal disorders is essential in preventing permanent or partial blindness. ...

Age and gender-related changes in choroidal thickness: Insights from deep learning analysis of swept-source OCT images.

BACKGROUND: The choroid is a vital vascular layer of the eye, essential for maintaining ocular healt...

Prompt injection attacks on vision language models in oncology.

Vision-language artificial intelligence models (VLMs) possess medical knowledge and can be employed ...

Automated strabismus detection and classification using deep learning analysis of facial images.

Strabismus, or eye misalignment, is a common condition affecting individuals of all ages. Early dete...

Autonomous Screening for Diabetic Macular Edema Using Deep Learning Processing of Retinal Images.

OBJECTIVE: To develop and validate a deep learning model for diabetic macular edema (DME) detection ...

U3UNet: An accurate and reliable segmentation model for forest fire monitoring based on UAV vision.

Forest fires pose a serious threat to the global ecological environment, and the critical steps in r...

Code-Free Deep Learning Glaucoma Detection on Color Fundus Images.

OBJECTIVE: Code-free deep learning (CFDL) allows clinicians with no coding experience to build their...

Enhancing furcation involvement classification on panoramic radiographs with vision transformers.

BACKGROUND: The severity of furcation involvement (FI) directly affected tooth prognosis and influen...

The case against machine vision for the control of wearable robotics: Challenges for commercial adoption.

Deploying machine vision for wearable robot control faces challenges in terms of usability, reliabil...

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