Ophthalmology

LensNet: An End-to-End Learning Framework for Empirical Point Spread Function Modeling and Lensless Imaging Reconstruction

Lensless imaging stands out as a promising alternative to conventional lens-based systems, particularly in scenarios demanding ultracompact form factors and cost-effective architectures. However, such systems are fundamentally governed by the Point Spread Function (PSF), which dictates how a point source contributes to the final captured signal. Traditional lensless techniques often require expl...

An LLM-Empowered Low-Resolution Vision System for On-Device Human Behavior Understanding

The rapid advancements in Large Vision Language Models (LVLMs) offer the potential to surpass conventional labeling by generating richer, more detailed descriptions of on-device human behavior understanding (HBU) in low-resolution vision systems, such as depth, thermal, and infrared. However, existing large vision language model (LVLM) approaches are unable to understand low-resolution data well...

Grounding Task Assistance with Multimodal Cues from a Single Demonstration

A person's demonstration often serves as a key reference for others learning the same task. However, RGB video, the dominant medium for representing...

Securing the Future of IVR: AI-Driven Innovation with Agile Security, Data Regulation, and Ethical AI Integration

The rapid digitalization of communication systems has elevated Interactive Voice Response (IVR) technologies to become critical interfaces for custo...

FalconWing: An Open-Source Platform for Ultra-Light Fixed-Wing Aircraft Research

We present FalconWing -- an open-source, ultra-lightweight (150 g) fixed-wing platform for autonomy research. The hardware platform integrates a sma...

Transferable Adversarial Attacks on Black-Box Vision-Language Models

Vision Large Language Models (VLLMs) are increasingly deployed to offer advanced capabilities on inputs comprising both text and images. While prior...

Robotic Visual Instruction

Recently, natural language has been the primary medium for human-robot interaction. However, its inherent lack of spatial precision introduces chall...

Visual Test-time Scaling for GUI Agent Grounding

We introduce RegionFocus, a visual test-time scaling approach for Vision Language Model Agents. Understanding webpages is challenging due to the vis...

AdCare-VLM: Leveraging Large Vision Language Model (LVLM) to Monitor Long-Term Medication Adherence and Care

Chronic diseases, including diabetes, hypertension, asthma, HIV-AIDS, epilepsy, and tuberculosis, necessitate rigorous adherence to medication to av...

Evaluation of AI Summaries on Interdisciplinary Understanding of Ophthalmology Notes.

IMPORTANCE: Specialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary ...

Novel Artificial Intelligence-Based Quantification of Anterior Chamber Inflammation Using Vision Transformers.

PURPOSE: Quantitative assessment of inflammation is critical for the accurate diagnosis and effective management of uveitis. This study aims to introd...

Development of machine learning-based models for vault prediction in implantable collamer lens surgery according to implant orientation.

PURPOSE: To develop a prediction model based on machine learning to calculate the postoperative vault and the ideal implantable collamer lens (ICL) si...

High-Accuracy Digitization of Humphrey Visual Field Reports Using Convolutional Neural Networks.

PURPOSE: Glaucoma is a leading cause of irreversible blindness worldwide, necessitating precise visual field (VF) assessments for effective diagnosis ...

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload as...

Intelligent Care Management for Diabetic Foot Ulcers: A Scoping Review of Computer Vision and Machine Learning Techniques and Applications.

Ten percent of adults in the United States have a diagnosis of diabetes and up to a third of these individuals will develop a diabetic foot ulcer (DFU...

An inherently interpretable AI model improves screening speed and accuracy for early diabetic retinopathy.

Diabetic retinopathy (DR) is a frequent complication of diabetes, affecting millions worldwide. Screening for this disease based on fundus images has ...

Artificial intelligence's contribution to biomedical literature search: revolutionizing or complicating?

There is a growing number of articles about conversational AI (i.e., ChatGPT) for generating scientific literature reviews and summaries. Yet, compara...

A Green Synchronous Fluorescence Analysis Approach for Simultaneous Determination of the Co-formulated Antihypertensives, Bisoprolol, and Amlodipine. Application to Plasma Samples, Market Formulations, Content Uniformity Test, and Greenness Evaluation.

In this study, we present a direct, sensitive, and green spectrofluorimetric approach for simultaneous measurement of bisoprolol fumarate (BSL) and am...

Artificial intelligence and machine learning in ocular oncology, retinoblastoma (ArMOR).

PURPOSE: To test the accuracy of a trained artificial intelligence and machine learning (AI/ML) model in the diagnosis and grouping of intraocular ret...

PhacoTrainer: Automatic Artificial Intelligence-Generated Performance Ratings for Cataract Surgery.

PURPOSE: To investigate whether cataract surgical skill performance metrics automatically generated by artificial intelligence (AI) models can differe...