Ophthalmology

Applications of Artificial Intelligence in Diagnosis of Dry Eye Disease: A Systematic Review and Meta-Analysis.

PURPOSE: Clinical diagnosis of dry eye disease is based on a subjective Ocular Surface Disease Index...

Development and evaluation of a deep neural network model for orthokeratology lens fitting.

PURPOSE: To optimise the precision and efficacy of orthokeratology, this investigation evaluated a d...

From vision to text: A comprehensive review of natural image captioning in medical diagnosis and radiology report generation.

Natural Image Captioning (NIC) is an interdisciplinary research area that lies within the intersecti...

Computer Vision and Videomics in Otolaryngology-Head and Neck Surgery: Bridging the Gap Between Clinical Needs and the Promise of Artificial Intelligence.

This article discusses the role of computer vision in otolaryngology, particularly through endoscopy...

Optimization of vision transformer-based detection of lung diseases from chest X-ray images.

BACKGROUND: Recent advances in Vision Transformer (ViT)-based deep learning have significantly impro...

Computational gastronomy: capturing culinary creativity by making food computable.

Cooking, a quintessential creative pursuit, holds profound significance for individuals, communities...

Clinical efficacy of pre-trained large language models through the lens of aphasia.

The rapid development of large language models (LLMs) motivates us to explore how such state-of-the-...

Learning feature relationships in CNN model via relational embedding convolution layer.

Establishing the relationships among hierarchical visual attributes of objects in the visual world i...

AI in Neuro-Ophthalmology: Current Practice and Future Opportunities.

BACKGROUND: Neuro-ophthalmology frequently requires a complex and multi-faceted clinical assessment ...

A mathematical theory of relational generalization in transitive inference.

Humans and animals routinely infer relations between different items or events and generalize these ...

Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence.

OBJECTIVES: This study aimed to quantitatively evaluate optic nerve head and retinal vascular parame...

Deep learning-based stress detection for daily life use using single-channel EEG and GSR in a virtual reality interview paradigm.

This research aims to establish a practical stress detection framework by integrating physiological ...

Adherence of studies involving artificial intelligence in the analysis of ophthalmology electronic medical records to AI-specific items from the CONSORT-AI guideline: a systematic review.

PURPOSE: In the context of ophthalmologic practice, there has been a rapid increase in the amount of...

Identification of key biomarkers for early warning of diabetic retinopathy using BP neural network algorithm and hierarchical clustering analysis.

Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by ab...

Automated eyeball volume measurement based on CT images using neural network-based segmentation and simple estimation.

With the increase in the dependency on digital devices, the incidence of myopia, a precursor of vari...

LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation.

Blinding eye diseases are often related to changes in retinal structure, which can be detected by an...

Using Pupil Diameter for Psychological Resilience Assessment in Medical Students Based on SVM and SHAP Model.

Effectively assessing psychological resilience for medical students is vital for identifying at-risk...

Prognosis Prediction of Diffuse Large B-Cell Lymphoma in F-FDG PET Images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and...

LDMRes-Net: A Lightweight Neural Network for Efficient Medical Image Segmentation on IoT and Edge Devices.

In this study, we propose LDMRes-Net, a lightweight dual-multiscale residual block-based convolution...

Continual pre-training mitigates forgetting in language and vision.

Pre-trained models are commonly used in Continual Learning to initialize the model before training o...

Artificial Intelligence-Based Ocular Motor Biomarkers for Myasthenia Gravis Diagnosis (P10-11.016).