AIMC Topic: Eye Diseases

Clear Filters Showing 1 to 10 of 129 articles

A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.

Medical science monitor : international medical journal of experimental and clinical research
Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical effici...

Neural network for natural language processing to determine treatment urgency in an ophthalmology emergency department.

The British journal of ophthalmology
BACKGROUND: In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial intelligence to develop a neural network and evaluate it...

Artificial Intelligence in Ocular Drug Delivery: Precision Drug Delivery's New Horizon.

AAPS PharmSciTech
BACKGROUND: Artificial intelligence is emerging as a transformative force in pharmaceutical sciences by enabling data-driven decision-making, automation, and predictive modeling. In ocular drug delivery, where therapeutic efficacy is hindered by comp...

Assessing the quality and educational applicability of AI-generated anterior segment images in ophthalmology.

Scientific reports
Text-to-image (T2I) artificial intelligence models are being increasingly explored in medical education, yet their utility in ophthalmology remains unclear. Slit-lamp anterior segment photography, as a cornerstone of ophthalmic training, provides an ...

Broad-spectrum eye disease classification using a deep learning-based tailored software lens.

PloS one
The early and accurate classification of eye diseases is essential for preventing irreversible visual impairment. This task can be performed by deep learning approaches that automatically classify retinal fundus images according to potential illnesse...

Leveraging fundus images for on device eye disease diagnosis with AI powered lightweight software hardware framework.

Scientific reports
Vision loss due to illness can result from various medical conditions that affect the eyes. Advanced devices like OCT and ultra-widefield retinal cameras are expensive, making them less accessible in resource-limited settings. While eye image capture...

Efficient fusion transformer model for accurate classification of eye diseases.

Scientific reports
The automatic diagnosis model of medical image based on deep learning can improve the diagnosis efficiency and reduce the diagnosis cost. At present, there is a lack of research on special artificial intelligence models for medical image analysis of ...

Evaluating the quality of ChatGPT-generated medical information on major ophthalmic conditions: A comparative assessment against the EQIP tool and guidelines.

PloS one
BACKGROUND: The use of artificial intelligence for creating medical information is on the rise. Nonetheless, the accuracy and reliability of such information require thorough assessment. As a language model capable of generating text, ChatGPT needs a...

Ocular implants and inserts: revolutionizing drug delivery in ophthalmology.

International journal of pharmaceutics
The ophthalmic route for drug administration remains a significant constraint in ophthalmology due to the unique anatomy and several protective barriers in the eyes, which limit absorption and therapeutic efficacy. Conventionally, drugs are delivered...

Multi-stage framework using transformer models, feature fusion and ensemble learning for enhancing eye disease classification.

Scientific reports
Eye diseases can affect vision and well-being, so early, accurate diagnosis is crucial to prevent serious impairment. Deep learning models have shown promise for automating the diagnosis of eye diseases from images. However, current methods mostly us...