Universal precautions

Physics-Informed Modeling of Biological Aging through DNA Methylation Entropy

Epigenetic clocks based on DNA methylation patterns are among the most accurate molecular correlates of chronological age, yet widely used clocks are predominantly empirical models with limited explicit characterization of the underlying methylation variability, lacking a direct connection to the physical mechanisms of aging. In this work, we bridge this gap by introducing an information-theoretic...

Hepatitis C Virus Genotyping with a Transformer Neural Network

This study aims to explore the applicability of Transformer-based models for genetic sequence classification by evaluating their performance in predicting hepatitis C virus (HCV) genotypes and subtypes after fine-tuning. A total of 2,881 HCV whole-genome sequences obtained from the Los Alamos HCV Sequence Database were used, including genotypes 1 to 6 and all confirmed subtypes. Genotypes 7 and 8 ...

TEAMS: Text-prompted spatiotEmporal dual-heAd Mamba Snake

Deep snake is a promising family of instance segmentation methods that accurately predicts object-level contours, thereby overcoming common pixel-leve...

GenRec: Knowing Where to Reconstruct and Where to Generate

Generative novel view synthesis from sparse input images is rarely all reconstruction or all generation: pixels visible in some source view have a uni...

A Configurable Privacy-Preserving MRI Processing Workflow Using Deep Learning-Based Brain Extraction and Adaptive Anatomical Preservation

Structural Magnetic Resonance Imaging (MRI) is widely used in neuroimaging research and clinical practice, but structural MRI volumes may retain facia...

Machine Learning Prediction of Antimicrobial Response in Pleurotus ostreatus Extracts Cultivated on Cassava Peel: A Proof-of-Concept Study

Antimicrobial resistance has intensified the search for sustainable natural products with antimicrobial properties. Pleurotus ostreatus cultivated on ...

FIRM: Fine-Grained Intra-Token Representation of Masks for Remote Sensing Reasoning Segmentation

Reasoning segmentation requires multimodal large language models (MLLMs) to translate implicit instructions into precise pixel-level masks. MLLMs enco...

Source-Agnostic Image Translation Based on Latent Aware Adaptive Masking

In this work, we propose a source-agnostic framework that dynamically refines a binary mask throughout the reverse diffusion process by computing the ...

PatchGen: Learning Soft Intra-Image Predictive Subsets for Visual Generalization

Visual classifiers are expected to generalize under data shifts, target shifts, and their combinations, yet most existing methods focus on domain inva...

DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation

Referring remote sensing image segmentation (RRSIS) aims to delineate targets specified by natural language expressions in remote sensing imagery. Exi...

Zero-OVCD: Bridging Training-Free Foundation Models and Pseudo-Label Learning for Open-Vocabulary Change Detection

Open-vocabulary change detection (OVCD) enables the identification of user-specified land-cover changes in bitemporal remote sensing images, but exist...

CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation

Semi-supervised histopathology segmentation is challenging due to scarce annotations and unreliable pseudo-labels in ambiguous gland regions. To addre...

AlbumentationsX: One Augmentation Pipeline for Images and Related Annotations

Augmentation can corrupt a training example when an image and its annotations receive different random changes. A crop must use the same coordinates f...

Detecting Clear Contact Lenses for Iris Recognition: A Two-Stage Mask-Guided Attention Approach

This work focuses on the impact and detection of clear contact lenses in the context of iris recognition. While the detection of cosmetic or patterned...

Contrastive Mask Fidelity: Reference-Free Auditing of Ground-Truth Masks in Remote Sensing Semantic Segmentation

Semantic segmentation models are trained and evaluated against human-drawn masks, yet remote-sensing annotations are often coarse, incomplete, or misa...

MedPixel: A Unified Pixel-Language Model for Medical Reasoning and Segmentation

Reliable medical image understanding requires models to connect clinical language and visual reasoning with pixel-level grounding. Yet medical vision-...

Deep learning-guided identification of bacteriophage receptor-binding protein candidates for foodborne pathogen detection

Foodborne pathogens including Salmonella spp., Escherichia coli and Listeria monocytogenes cause an estimated 600 million illnesses annually. Yet conv...

Multimodal artificial intelligence using entire electronic health record and complete pathogen genome data for patient outcome prediction from life-threatening infection: the SuperbugAI Platform

Artificial intelligence (AI) has the potential to transform healthcare, with advanced multimodal approaches showing great promise in leveraging divers...

Universal Concept Disruption for SAM3 Image Segmentation

SAM3 extends promptable segmentation from geometry-driven mask prediction to open-vocabulary concept segmentation, where a text-conditioned grounding ...

TLNM: Externally Validated Tooth Detection, Numbering and Segmentation from Smartphone Photographs Using Mask R-CNN

Oral health issues affect billions globally, but the cost and limited access to professional dental care hinder preventive oral healthcare. Research r...