Latest AI and machine learning research in ophthalmology for healthcare professionals.
Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear layer, with an upward expansion of the outer nuclear layer identified by spectral domain optical coherence tomography (SD-OCT), causing a focal irregular appearance of the middle retina. RIPLs result from retinal hypoperfusion in the deep capillary plexus, as a legacy of paracentral acute middle ma...
Ophthalmology, like all medical specialities, is continuously evolving to adapt to emerging challenges and advancements. The evidence-based medical practices that previously guided policies and regulations may no longer be sufficient or sustainable in the context of an ageing population, increasing healthcare demands, and the urgent need for sustainability. As the global burden on healthcare syste...
BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to develop a model for predicting OHT progression to ...
PURPOSE: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. Th...
Developmental and epileptic encephalopathies (DEEs) are severe neurological disorders characterized by childhood-onset seizures and significant develo...
Leveraging real-time eye tracking, foveated rendering optimizes hardware efficiency and enhances visual quality virtual reality (VR). This approach le...
INTRODUCTION: Children with Developmental Coordination Disorder (DCD) experience impairments beyond motor planning, affecting visual perceptual and vi...
Digital pathology (DP) has significantly transformed breast pathology at Mount Sinai Hospital by enhancing diagnostic accuracy, collaboration, and edu...
The early minor faults generated by the chiller in operation are not easy to perceive, and the severity will gradually increase with time. The traditi...
BACKGROUND: Retinopathy of prematurity (ROP) is the leading preventable cause of childhood blindness. A timely intravitreal injection of antivascular ...
Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stag...
Trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, has emerged as a potential contributor to diabetic retinopathy (DR) progression. H...
. This study is focused on creating an effective glaucoma detection system employing a Hybrid Centric Convolutional Neural Network (HCCNN) model. By u...
Accurate anatomical measurements of the eyelids are essential in periorbital plastic surgery for both disease treatment and procedural planning. Recen...
Detecting Alzheimer's disease (AD) in its earliest stages, particularly during an onset of Mild Cognitive Impairment (MCI), remains challenging due to...
PRCIS: The AI model, enhanced by SMOTE to balance data classes, accurately predicted visual field deterioration in patients with myopic normal tension...
PURPOSE OF REVIEW: Advances in artificial intelligence have integrated into modern medicine decision making and diagnostics. Artificial intelligence i...
The integration of multimodal capabilities into GPT-4 represents a transformative leap for artificial intelligence in ophthalmology, yet its utility ...
Automated identification of retinal landmarks, particularly the fovea is crucial for diagnosing diabetic retinopathy and other ocular diseases. But ac...
Turnaround time (TAT) has evolved into a complex metric in the current era of diagnostic radiology. Initially monitoring a radiologist's ability to ef...