AIMC Topic: Eye Diseases

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Effectiveness of smartphone technology for detection of paediatric ocular diseases-a systematic review.

BMC ophthalmology
BACKGROUND: Artificial intelligence has become part of healthcare with a multitude of applications being customized to roles required in clinical practice. There has been an expanding growth and development of computer technology with increasing appe...

Advancements in artificial intelligence for the diagnosis and management of anterior segment diseases.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The integration of artificial intelligence (AI) in the diagnosis and management of anterior segment diseases has rapidly expanded, demonstrating significant potential to revolutionize clinical practice.

Advancing ocular gene therapy: a machine learning approach to enhance delivery, uptake and gene expression.

Drug discovery today
Ocular gene therapy offers a promising approach for treating various eye diseases, centered on the process of transfection, including delivery, cellular uptake and gene expression. This study addresses anatomical and physiological barriers, such as t...

Can off-the-shelf visual large language models detect and diagnose ocular diseases from retinal photographs?

BMJ open ophthalmology
BACKGROUND: The advent of generative artificial intelligence has led to the emergence of multiple vision large language models (VLLMs). This study aimed to evaluate the capabilities of commonly available VLLMs, such as OpenAI's GPT-4V and Google's Ge...

Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence.

Medicina (Kaunas, Lithuania)
The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering new opportunities to enhance diagnostic accuracy, personalize treatment plans, and improve service delivery. This review provides a comprehensive ove...

HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification.

Scientific reports
Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventional CNN-based models face limitations such as high computational overhead, noise sensitivity, and data imbalance. This paper introduces HDL-ACO, a nov...

EAMAPG: Explainable Adversarial Model Analysis via Projected Gradient Descent.

Computers in biology and medicine
Despite the outstanding performance of deep learning (DL) models, their interpretability remains a challenging topic. In this study, we address the transparency of DL models in medical image analysis by introducing a novel interpretability method usi...

Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases.

Scientific reports
CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed for its impact on ophthalmologists' diagnostic accuracy. In the study, 40 ophthalmologists (20 specialists and 20 residents) classified 100 images, in...

Optimising deep learning models for ophthalmological disorder classification.

Scientific reports
Fundus imaging, a technique for recording retinal structural components and anomalies, is essential for observing and identifying ophthalmological diseases. Disorders such as hypertension, glaucoma, and diabetic retinopathy are indicated by structura...

Advancements and Prospects in Nanorobotic Applications for Ophthalmic Therapy.

ACS biomaterials science & engineering
This study provides a bibliometric and bibliographic review of emerging applications of micro- and nanotechnology in treating ocular diseases, with a primary focus on glaucoma. We aim to identify key research trends and analyze advancements in device...