Ophthalmology

Smartphone Eye Examination: Artificial Intelligence and Telemedicine.

The current medical scenario is closely linked to recent progress in telecommunications, photodocumentation, and artificial intelligence (AI). Smartphone eye examination may represent a promising tool in the technological spectrum, with special interest for primary health care services. Obtaining fundus imaging with this technique has improved and democratized the teaching of fundoscopy, but in p...

In-line particle size measurement during granule fluidization using convolutional neural network-aided process imaging.

This paper presents a machine learning-based image analysis method to monitor the particle size distribution of fluidized granules. The key components of the direct imaging system are a rigid fiber-optic endoscope, a light source and a high-speed camera, which allow for real-time monitoring of the granules. The system was implemented into a custom-made 3D-printed device that could reproduce the pa...

Customization of a passive surgical support robot to specifications for ophthalmic surgery and preliminary evaluation.

PURPOSE: To customize a passive surgery support robot for ophthalmic surgery and preliminarily evaluate its performance.

Evaluating the potential of ChatGPT-4 in ophthalmology: The good, the bad and the ugly.

There is growing interest nowadays for artificial intelligence (AI) in all medical fields. Beyond the direct medical application of AI to medical data...

A conceptual framework of cognitive-affective theory of mind: towards a precision identification of mental disorders.

To explore the minds of others, which is traditionally referred to as Theory of Mind (ToM), is perhaps the most fundamental ability of humans as socia...

Artificial intelligence chatbot performance in triage of ophthalmic conditions.

BACKGROUND: Timely access to human expertise for affordable and efficient triage of ophthalmic conditions is inconsistent. With recent advancements in...

An advanced deep learning method to detect and classify diabetic retinopathy based on color fundus images.

BACKGROUND: In this article, we present a computerized system for the analysis and assessment of diabetic retinopathy (DR) based on retinal fundus pho...

Deep-learning detection of mild cognitive impairment from sleep electroencephalography for patients with Parkinson's disease.

Parkinson's disease which is the second most prevalent neurodegenerative disorder in the United States is a serious and complex disease that may progr...

A deep learning approach to investigate the filtration bleb functionality after glaucoma surgery: a preliminary study.

PURPOSE: To distinguish functioning from failed filtration blebs (FBs) implementing a deep learning (DL) model on slit-lamp images.

Imagining machine vision: Four visual registers from the Chinese AI industry.

Machine vision is one of the main applications of artificial intelligence. In China, the machine vision industry makes up more than a third of the nat...

Success of ChatGPT, an AI language model, in taking the French language version of the European Board of Ophthalmology examination: A novel approach to medical knowledge assessment.

PURPOSE: The purpose of this study was to evaluate the performance of ChatGPT, a cutting-edge artificial intelligence (AI) language model developed by...

Comparison of Ophthalmologist and Large Language Model Chatbot Responses to Online Patient Eye Care Questions.

IMPORTANCE: Large language models (LLMs) like ChatGPT appear capable of performing a variety of tasks, including answering patient eye care questions,...

Risk of Induction of Corneal Neovascularization with Topical Erythropoietin: An Animal Safety Study.

PURPOSE: To evaluate the pro-angiogenic effect of topical erythropoietin on cornea in chemical burn-injured rabbit eyes.

Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.

BACKGROUND: The use of artificial intelligence is becoming more prevalence in medicine with numerous successful examples in ophthalmology. However, mu...

Rapid eye movement sleep loss associated cytomorphometric changes and neurodegeneration.

Rapid eye movement sleep (REMS) is essential for leading normal healthy living at least in higher-order mammals, including humans. In this review, we ...

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization.

Optical coherence tomography (OCT) is widely used to detect and classify retinal diseases. However, OCT-image-based manual detection by ophthalmologis...

Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, ...

Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?

UNLABELLED: - Objective: To explore the clinical validity of elastic deformation of optical coherence tomography (OCT) images for data augmentation in...

Attention-based deep learning framework to recognize diabetes disease from cellular retinal images.

A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many people are visually impaired due to DR. Primary ca...

Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia.

PRCIS: An optical coherence tomography (OCT)-based multimodal deep learning (DL) classification model, including texture information, is introduced th...