Ophthalmology

Distinct Tumor-Immune Ecologies in Patients with Lung Cancer Predict Progression and Define a Clinical Biomarker of Therapy Response.

UNLABELLED: Multiplexed imaging of tissues is an approach that holds promise for improving early detection, diagnosis, and treatment of cancer. In this study, we investigated multiplexed histologic images of paired pretreatment and on-treatment samples from nine patients with immunotherapy-refractory non-small cell lung cancer (NSCLC) treated with an oral histone deacetylase inhibitor (vorinostat)...

Benchmarking multiple instance learning architectures from patches to pathology for prostate cancer detection and grading using attention-based weak supervision.

Histopathological evaluation is necessary for the diagnosis and grading of prostate cancer, which is still one of the most common cancers in men globally. Traditional evaluation is time-consuming, prone to inter-observer variability, and challenging to scale. The clinical usefulness of current AI systems is limited by the need for comprehensive pixel-level annotations. The objective of this resear...

Single capture quantitative oblique back-illumination microscopy.

Quantitative oblique back-illumination microscopy (qOBM) has emerged as a powerful technique for label-free, 3D quantitative phase imaging of arbitrar...

A test-time clinically adaptive framework for detecting multiple fundus diseases harnessing ophthalmic foundation models.

Fundus diseases are leading causes of global vision impairment, often presenting with complex comorbidities that challenge conventional artificial int...

Kolmogorov-Arnold networks for data-driven, physics-informed, and deep-operator learning: a review, synthesis, and new analysis.

The field of scientific machine learning, which originally utilized multilayer perceptrons (MLPs), is increasingly adopting Kolmogorov-Arnold Networks...

MedFusionT5: Cross-Modal Attention Boosts Semantic Quality and Reduces Hallucinations in Dental AI.

INTRODUCTION AND AIMS: Automated dental report generation faces significant challenges in multimodal fusion, often resulting in suboptimal semantic qu...

CHOROIDAL VASCULARITY INDEX, RETINAL VASCULARITY, AND HEMOGLOBIN LEVELS IN PEDIATRIC SICKLE CELL MACULOPATHY.

PURPOSE: To evaluate the choroidal vascularity index (CVI) in pediatric patients with sickle cell disease (SCD) and its associations with retinal thic...

Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models.

Deep neural networks (DNNs) have proven to be successful in various computer vision applications such that models even infer in safety-critical situat...

DIAGNOSTIC PERFORMANCE OF MACHINE LEARNING TECHNOLOGY USING OPTICAL COHERENCE TOMOGRAPHIC IMAGE IN RETINAL DISEASES PRESENTED WITH SUBRETINAL FLUID.

PURPOSE: To study the diagnostic performance of machine learning in the diagnosis of three retinal diseases presented with subretinal fluid: central s...

Real-World Prospective Validation and Economic Evaluation of Deep Learning- Based Diabetic Retinopathy Detection From Fundus Photographs: A Systematic Review and Meta-analysis.

BACKGROUND: Deep learning (DL) has shown promise in delivering diagnostic and economic benefits for detecting diabetic retinopathy (DR) from fundus ph...

Self-Supervised Text-Vision Alignment for Automated Brain MRI Abnormality Detection: A Multicenter Study (ALIGN Study).

Purpose To develop a self-supervised text-vision framework to detect abnormalities on brain MRI scans by leveraging free-text neuroradiology reports, ...

Updates in Central Retinal Artery Occlusion.

BACKGROUND: Central retinal artery occlusion (CRAO) is a vision-threatening neuro-ophthalmic emergency, analogous to acute ischemic stroke. Delayed pr...

Inverse design method of optical devices for generating target near-fields via physics-informed neural networks.

We propose a method for inverse design of optical devices to generate target near-fields using physics-informed neural networks (PINNs). A finite-diff...

Tape-assisted nanoplasmonic biosensors for facile protein-on-chip visualization and multiplexed point-of-care diagnostics.

Visual point-of-care testing (POCT) technologies convert biomolecular events into naked-eye readable signals. These systems offer rapid assay times, u...

Organic Optoelectronic Memristor Inspired by Insect Ultraviolet Vision for Attention Mechanism Simulation.

The rapid evolution of modern technology is propelling artificial intelligence into a transformative phase, where visual information processing has be...

Generative models of cell dynamics: from Neural ODEs to flow matching.

Neural Ordinary Differential Equations (Neural ODEs) have emerged as a prominent framework for modeling complex dynamical systems. Their ability to de...

Deep Learning Model to Detect Diabetic Retinopathy in 45° Images Using Ground Truth from Ultra-Widefield Imaging.

PURPOSE: To evaluate the performance of a deep learning (DL) model in classifying diabetic retinopathy (DR) severity using fundus images with varying ...

Identification of extracellular matrix stiffness-related genes in human scleral fibroblasts through bioinformatics analysis and machine learning.

BACKGROUND: Scleral extracellular matrix (ECM) remodeling plays a key role in myopia development. This study aims to identify ECM stiffness-related ge...

Artificial intelligence in glaucoma diagnosis and management: Has its time come?

Adaptive Temporal Mixture of Experts for Predicting Stiffness Metrics from the Ocular Response Analyzer and Identifying Keratoconus: Stiffness Estimates from Ocular Response Analyzer.

PURPOSE: To develop a machine learning-based modeling approach for extracting elastic stiffness estimates from Ocular Response Analyzer (ORA) waveform...