Latest AI and machine learning research in ophthalmology for healthcare professionals.
PURPOSE: To characterize the choroidal morphology across a spectrum of participants affected by normal aging as well as age-related macular degeneration (AMD) using various metrics. METHODS: Four cohorts were analyzed: healthy young (n = 42), healthy elderly (n = 19), iAMD (n = 20), and treatment-naive nAMD eyes (n = 79). Quantification of choroidal volume (CV) and choroidal vessel volume (VV) res...
INTRODUCTION: Precise intraocular lens (IOL) positioning is critical for optimal visual outcomes in cataract surgery, particularly with advanced IOLs. Misalignment can lead to refractive errors, astigmatism, and higher-order aberrations. This study aimed to predict postoperative anterior chamber depth (ACD), IOL tilt, and decentration using machine learning. METHODS: A prospective, single-center s...
Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods...
BACKGROUND: Conversational agents (CAs) are increasingly used in mental health care to enhance access and engagement. However, their safe, ethical, an...
Based on dual-stage attention recurrent neural network (DA-RNN), a masked DA-RNN (MDA-RNN) model was developed to predict future visual fields (VF). T...
Anti-vascular endothelial growth factor (anti-VEGF) therapy is the mainstay of management for diabetic macular edema (DME), but marked variability in ...
OBJECTIVES: Globally, dental reforms have gained momentum through enhanced policy dialogues, the rise of digital health, artificial intelligence and o...
The rapid rise of artificial intelligence, and in-memory computing has reinvigorated research on scalable, energy-efficient, and reconfigurable photon...
BACKGROUND: Cataracts are an eye condition characterized by high prevalence and blindness-inducing potential, and effective approaches are required fo...
OBJECTIVES: Automated segmentation of retinal blood vessels in optical coherence tomography angiography (OCTA) images is essential for early diagnosis...
Sleep stage classification based on electroencephalography (EEG) is fundamental for assessing sleep quality and diagnosing sleep-related disorders. Ho...
BACKGROUND: Colorectal cancer is a major global health burden, with most cases arising from adenomatous polyps. Although colonoscopy is the gold stand...
Accuracy and duration of ocular pursuit of a target object have been linked to interceptive performance. Yet, previous assessments have not examined t...
BACKGROUND: The escalating prevalence of screen-related eye fatigue has become a health burden in the digital era worldwide, yet routine monitoring re...
The rapid integration of artificial intelligence (AI) into clinical practice necessitates urgent restructuring of medical education and physician asse...
PURPOSE: To develop a machine learning (ML)-driven polygenic risk score (PRS) for diabetic retinopathy (DR) and evaluate the extent to which lifestyle...
Although computer vision approaches based on machine learning (ML) and deep learning (DL) have been applied to image-based food quality analysis, they...
To address the challenges of achieving organic compliance in kitchen wastewater treatment and the high cost of chemical dosing, this study established...
BACKGROUND: Anxiety disorders are highly prevalent yet lack objective biomarkers. Whereas threat-related attentional biases are well documented, less ...
OBJECTIVES: The gut microbiome-gut-brain axis (MGBA) has been associated in the pathophysiology of depression; however, the expanding literature remai...