Ophthalmology

The Epistemological Nuances of Interpreting Adaptive Machine Learning Systems Through the Lens of Surgical Innovation.

Role of Artificial Intelligence in Retinal Diseases.

Artificial intelligence (AI) has already found its way into ophthalmology, with the first approved algorithms that can be used in clinical routine. Retinal diseases in particular are proving to be an important area of application for AI, as they are the main cause of blindness and the number of patients suffering from retinal diseases is constantly increasing. At the same time, regular imaging usi...

Gemini AI vs. ChatGPT: A comprehensive examination alongside ophthalmology residents in medical knowledge.

INTRODUCTION: The rapid advancement of artificial intelligence (AI), particularly in large language models like ChatGPT and Google's Gemini AI, marks ...

Deep feature fusion with computer vision driven fall detection approach for enhanced assisted living safety.

Assisted living facilities cater to the demands of the elderly population, providing assistance and support with day-to-day activities. Fall detection...

Exploring Artificial Intelligence Programs' Understanding of Lens, Cataract, and Refractive Surgery Information.

PURPOSE: We aimed to evaluate the success of Chat Generative Pre-trained Transformer (ChatGPT), Bing, and Bard artificial intelligence programs, which...

Diagnostic Performance of the Offline Medios Artificial Intelligence for Glaucoma Detection in a Rural Tele-Ophthalmology Setting.

PURPOSE: This study assesses the diagnostic efficacy of offline Medios Artificial Intelligence (AI) glaucoma software in a primary eye care setting, u...

An attentional mechanism model for segmenting multiple lesion regions in the diabetic retina.

Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the precise segmentation of lesions for the effective gradi...

Exploring the Global Reaction Coordinate for Retinal Photoisomerization: A Graph Theory-Based Machine Learning Approach.

Unraveling the reaction pathway of photoinduced reactions poses a great challenge owing to its complexity. Recently, graph theory-based machine learni...

Oscillations in an artificial neural network convert competing inputs into a temporal code.

The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development...

Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging.

BACKGROUND: A whole person approach to healthy aging can provide insight into social factors that may be critical. Digital technologies, such as mobil...

Artificial intelligence for geographic atrophy: pearls and pitfalls.

PURPOSE OF REVIEW: This review aims to address the recent advances of artificial intelligence (AI) in the context of clinical management of geographic...

Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?

PURPOSE OF REVIEW: Given the increasing global burden of diabetic retinopathy and the rapid advancements in artificial intelligence, this review aims ...

Validation of neuron activation patterns for artificial intelligence models in oculomics.

Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the field of oculomics; the association between the retin...

Integrating AI with tele-ophthalmology in Canada: a review.

The field of ophthalmology is rapidly advancing, with technological innovations enhancing the diagnosis and management of eye diseases. Tele-ophthalmo...

Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.

Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable...

Handling missing data and measurement error for early-onset myopia risk prediction models.

BACKGROUND: Early identification of children at high risk of developing myopia is essential to prevent myopia progression by introducing timely interv...

Optoelectronic neuron based on transistor combined with volatile threshold switching memristors for neuromorphic computing.

The human perception and learning heavily rely on the visual system, where the retina plays a vital role in preprocessing visual information. Developi...

Comparison review of image classification techniques for early diagnosis of diabetic retinopathy.

Diabetic retinopathy (DR) is one of the leading causes of vision loss in adults and is one of the detrimental side effects of the mass prevalence of D...

Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera.

OBJECTIVES: Despite global research on early detection of age-related macular degeneration (AMD), not enough is being done for large-scale screening. ...

Deep learning approach for detecting tomato flowers and buds in greenhouses on 3P2R gantry robot.

In recent years, significant advancements have been made in the field of smart greenhouses, particularly in the application of computer vision and rob...