Latest AI and machine learning research in ophthalmology for healthcare professionals.
IMPORTANCE: A deep learning (DL) model capable of analyzing optical coherence tomography (OCT) 3-dimensional (3D) scans from various vendors is essential for robust disease detection. OBJECTIVE: To develop a vendor-agnostic model for multidisease classification using 3D scans from different vendors. DESIGN, SETTING, AND PARTICIPANTS: This multicenter retrospective cohort study included OCT scans f...
BACKGROUND/AIMS: Patients have largely been excluded from discussions on the use of their health data in developing medical artificial intelligence (AI), despite being directly affected by its integration into care. This study assessed ophthalmology patients' perspectives on AI to inform patient-aligned development and implementation. METHODS: We conducted a cross-sectional survey across ophthalmo...
Catecholaminergic polymorphic ventricular tachycardia is a classic example of the successful transfer of genetic cardiology from gene discovery to imp...
Inspired by the dynamic visual perception of flying insects, rapid collision warning systems are crucial for advancing autonomous driving and machine ...
ConspectusPhoton upconversion, which converts low-energy near-infrared light into higher-energy emission, has emerged as a powerful tool at the inters...
Plasmonic sensing is a vibrant field where the optical properties of surface plasmons are exploited to create analytical sensors for biomedical, envir...
Underserved communities in the United States continue to face substantial barriers to accessing eye care, leading to preventable vision loss. This rev...
BACKGROUND: Artificial intelligence (AI) promises to significantly impact daily radiology practices. Numerous studies have already been conducted that...
It is increasingly recognized that learning and memory depend, not only on changes in synaptic strength, but also on experience-dependent modification...
PURPOSE: To evaluate early morphological changes following intravitreal aflibercept 8 mg in treatment-naïve neovascular age-related macular degenerati...
Considerations around model retraining are standard practice in industry and non-healthcare sectors; however, this is much less well explored in medic...
The purpose is to evaluate whether numeric optical coherence tomography (OCT) data can predict Humphrey Visual Field Analyzer (HFA) 30-2 mean deviatio...
The Forward-Forward (FF) algorithm was recently proposed as a local learning method to address the limitations of backpropagation (BP), offering a mem...
PURPOSE: To develop a deep learning (DL) model for diagnosing ocular surface tumors and evaluating its diagnostic performance. SETTING: Development of...
PRECIS: Artificial intelligence-derived macular thinning patterns were associated with central visual field progression in glaucoma and outperformed g...
BACKGROUND: Uveal melanoma (UM), the most common form of ocular melanoma, represents poor prognosis, with approximately 50% of patients developing met...
CLINICAL RELEVANCE: Assistive smartphone apps play an integral role in supporting people with vision impairment (VI). Low vision rehabilitation (LVR) ...
Accurate fovea segmentation in fundus images is a critical step in diabetic retinopathy screening; however, it remains a challenging task due to the i...
Ultrasound imaging has played an important role in ophthalmic diagnostics due to its real-time capability, safety, and cost-effectiveness. In recent y...