Comparative Analysis of Transformer Architectures and Ensemble Methods for Automated Glaucoma Screening in Fundus Images from Portable Ophthalmoscopes [0.03%]
基于便携式眼底相机眼底图像的自动化青光眼筛查的变压器架构和集成方法比较分析
Rodrigo Otávio Cantanhede Costa,Pedro Alexandre Ferreira França,Alexandre César Pinto Pessoa et al.
Rodrigo Otávio Cantanhede Costa et al.
Deep learning for glaucoma screening often relies on high-resolution clinical images and convolutional neural networks (CNNs). However, these methods face significant performance drops when applied to noisy, low-resolution images from porta...
Biases in Perceiving Positive Versus Negative Emotions: The Influence of Social Anxiety and State Affect [0.03%]
社会焦虑和心境状态对消极与积极情绪知觉偏差的影响
Vivian M Ciaramitaro,Erinda Morina,Jenny L Wu et al.
Vivian M Ciaramitaro et al.
Models suggest social anxiety is characterized by negative processing biases. Negative biases also arise from negative mood, i.e., state affect. We examined how social anxiety influences emotional processing and whether state affect, or moo...
In-Vivo Characterization of Healthy Retinal Pigment Epithelium and Photoreceptor Cells from AO-(T)FI Imaging [0.03%]
基于AO-(T)FI成像的健康视网膜色素上皮细胞和光感受器细胞的体内表征研究
Sohrab Ferdowsi,Leila Sara Eppenberger,Safa Mohanna et al.
Sohrab Ferdowsi et al.
We provide an automated characterization of human retinal cells, i.e., RPE's based on the non-invasive AO-TFI retinal imaging and PR's based on the non-invasive AO-FI retinal imaging on a large-scale study involving 171 confirmed healthy ey...
Sudi Patel,Larysa Tutchenko,Igor Dmytruk
Sudi Patel
Background: This paper aims to provide an overview of corneal birefringence (CB), systematize the knowledge and current understanding of CB, and identify difficulties associated with introducing CB into mainstream clinica...
Prevalence of Keratoconus and Associated Risk Factors Among High School Students in Couva, Trinidad: A Cross-Sectional Study [0.03%]
特立尼达库瓦地区高中生角膜扩张患病率及其危险因素的横断面研究
Ngozika Esther Ezinne,Shinead Phagoo,Ameera Roopnarinesingh et al.
Ngozika Esther Ezinne et al.
Purpose: This study aimed to determine the prevalence and associated risk factors of keratoconus (KC) among high school students in Couva, Trinidad and Tobago. Method: A cross-sectional, school-based approach was used, involving a simple ra...
Comparing Visual Search Efficiency Across Different Facial Characteristics [0.03%]
基于不同面部特征的视觉搜索效率对比分析
Navdeep Kaur,Isabella Hooge,Andrea Albonico
Navdeep Kaur
Face recognition is an important skill that helps people make social judgments by identifying both who a person is and other characteristics such as their expression, age, and ethnicity. Previous models of face processing, such as those pro...
Development of a Neural Network to Predict Optimal IOP Reduction in Glaucoma Management [0.03%]
开发用于预测青光眼管理中最佳眼内压降低的神经网络
Raheem Remtulla,Sidrat Rahman,Hady Saheb
Raheem Remtulla
Glaucoma management relies on lowering intraocular pressure (IOP), but determining the target reduction at presentation is challenging, particularly in normal-tension glaucoma (NTG). We developed and internally validated a neural network re...
Clinical Assessment of a Virtual Reality Perimeter Versus the Humphrey Field Analyzer: Comparative Reliability, Usability, and Prospective Applications [0.03%]
虚拟现实视野计与Humphrey视野计的临床评估：可靠性、可用性和前瞻性应用的比较
Marco Zeppieri,Caterina Gagliano,Francesco Cappellani et al.
Marco Zeppieri et al.
Background: This study compared the performance of a Head-mounted Virtual Reality Perimeter (HVRP) with the Humphrey Field Analyzer (HFA), the standard in automated perimetry. The HFA is the established standard for automated perimetry but ...
Comparative Assessment of Large Language Models in Optics and Refractive Surgery: Performance on Multiple-Choice Questions [0.03%]
用于屈光手术的大型语言模型在多项选择题上的性能比较评估
Leah Attal,Elad Shvartz,Alon Gorenshtein et al.
Leah Attal et al.
This study aimed to evaluate the performance of seven advanced AI Large Language Models (LLMs)-ChatGPT 4o, ChatGPT O3 Mini, ChatGPT O1, DeepSeek V3, DeepSeek R1, Gemini 2.0 Flash, and Grok-3-in answering multiple-choice questions (MCQs) in ...
Rajat S Chandra,Bole Ying,Jianyong Wang et al.
Rajat S Chandra et al.
We previously developed machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) and myopia using non-cycloplegic data and following a standardized protocol (cycloplegia with 0.5% tropicamide and biometr...