Ophthalmology

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

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Artificial intelligence in ophthalmology.

PURPOSE OF REVIEW: To review role of artificial intelligence in medicine.

Evaluating the reproducibility of a deep learning algorithm for the prediction of retinal age.

Recently, a deep learning algorithm (DLA) has been developed to predict the chronological age from r...

The use of artificial intelligence based chat bots in ophthalmology triage.

PURPOSE: To evaluate AI-based chat bots ability to accurately answer common patient's questions in t...

Advancements in microsurgery: A comprehensive systematic review of artificial intelligence applications.

Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn fr...

Spike-VisNet: A novel framework for visual recognition with FocusLayer-STDP learning.

Current vision-inspired spiking neural networks (SNNs) face key challenges due to their model struct...

Detection of retinal diseases using an accelerated reused convolutional network.

Convolutional neural networks are continually evolving; with some efforts aimed at improving accurac...

Investigating streetscape environmental characteristics associated with road traffic crashes using street view imagery and computer vision.

Examining the relationship between streetscape features and road traffic crashes is vital for enhanc...

Research on machine vision online monitoring system for egg production and quality in cage environment.

In the domain of egg production, the application of automation technologies is essential for boostin...

Artificial Intelligence to Diagnose Complications of Diabetes.

Artificial intelligence (AI) is increasingly being used to diagnose complications of diabetes. Artif...

Unsupervised Learning-Assisted Acoustic-Driven Nano-Lens Holography for the Ultrasensitive and Amplification-Free Detection of Viable Bacteria.

Bacterial infection is a crucial factor resulting in public health issues worldwide, often triggerin...

Robust diabetic prediction using ensemble machine learning models with synthetic minority over-sampling technique.

This paper addresses the pressing issue of diabetes, which is a widespread condition affecting a hug...

Predicting the cognitive impairment with multimodal ophthalmic imaging and artificial neural network for community screening.

BACKGROUND/AIMS: To investigate the comprehensive prediction ability for cognitive impairment in a g...

The use of machine learning to understand the role of visual attention in multi-attribute choice.

Whether eye movements (as a measure of visual attention) contribute to the understanding of how mult...

Using machine learning to identify pediatric ophthalmologists.

This cross-sectional study used data from the American Academy of Ophthalmology IRIS Registry (Intel...

Applications of artificial intelligence to inherited retinal diseases: A systematic review.

Artificial intelligence(AI)-based methods have been extensively used for the detection and managemen...

Artificial intelligence in assessing progression of age-related macular degeneration.

The human population is steadily growing with increased life expectancy, impacting the prevalence of...

Discrimination of wheat gluten quality utilizing terahertz time-domain spectroscopy (THz-TDS).

Wheat is an important food crop in the world, and wheat gluten quality is one of the important stand...

Quantum Computing in Medicine.

Quantum computing (QC) represents a paradigm shift in computational power, offering unique capabilit...

Enhanced breast cancer diagnosis through integration of computer vision with fusion based joint transfer learning using multi modality medical images.

Breast cancer (BC) is a type of cancer which progresses and spreads from breast tissues and graduall...

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