Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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iTRIALSPACE: Programmable Virtual Lesion Trials for Controlled Evaluation of Lung CT Models

We introduce iTRIALSPACE, a programmable evaluation framework for controlled assessment of lung CT m...

Combinatorial epigenomic patterns define regulatory programs underlying disease heterogeneity

Disease is a heterogeneous process that involves multiple organs and cell types. Understanding how g...

deSEO: Physics-Aware Dataset Creation for High-Resolution Satellite Image Shadow Removal

Shadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite im...

Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers

Visual affordances identify regions in an image with potential interactions, offering a novel paradi...

Biological Spatial Priors Regularize Foundation Model Representations for Cross-Site MSI Generalization in Colorectal Cancer

Predicting microsatellite instability (MSI) status from routine hematoxylin and eosin (H&E) whole sl...

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

The incidence of the vast majority of neurodegenerative, cancer, and metabolic diseases generally in...

Exploring the Limits of End-to-End Feature-Affinity Propagation for Single-Point Supervised Infrared Small Target Detection

Single-point supervised infrared small target detection (IRSTD) drastically reduces dense annotation...

Tuned inhibitory control of neuronal firing thresholds explains predictive sensorimotor behavior

Prior expectations guide sensorimotor behavior when sensory information is uncertain, yet the cellul...

Remote SAMsing: From Segment Anything to Segment Everything

SAM2 produces high-quality zero-shot segmentation on natural images, but applying it to large remote...

Overcoming systematic data biases enables accurate prediction of enzyme kcat fold-changes for computational protein design

Machine learning is increasingly used to guide protein engineering by predicting how mutations affec...

Artificial Intelligence for Cardiac Biomarkers After Myocardial Infarction: A Systematic Review and a Leakage-Aware Modeling Framework

Aims To systematically evaluate how artificial intelligence and machine-learning (AI/ML) methods are...

Explainable Prototype Booster: Enhancing Latent Representations of Foundation Models for Gene Expression Prediction

Spatial transcriptomics (ST) is a cutting-edge technology that measures gene expression while preser...

Are Data Augmentation and Segmentation Always Necessary? Insights from COVID-19 X-Rays and a Methodology Thereof

Purpose: Rapid and reliable diagnostic tools are crucial for managing respiratory diseases like COVI...

Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models

Diffusion models have achieved remarkable success in synthesizing complex static and temporal visual...

Deep-testing: the case of dependence detection

Deep learning methods have proved highly effective for classification and image recognition problems...

One Perturbation, Two Failure Modes: Probing VLM Safety via Embedding-Guided Typographic Perturbations

Typographic prompt injection exploits vision language models' (VLMs) ability to read text rendered i...

UshEffect-3D: Structure-informed Classification of USH2A Missense Variants for Inherited Retinal Disease

Variants of uncertain significance (VUS) in USH2A represent a critical interpretive challenge in inh...

Combining AI structure prediction and integrative modelling for nanobody-antigen complexes

Nanobodies exhibit antigen binding a[ffi]nities of the same order as those of antibodies, which, alo...

DiffuSAM: Diffusion-Based Prompt-Free SAM2 for Few-Shot and Source-Free Medical Image Segmentation

Segmentation models such as Segment Anything Model (SAM) and SAM2 achieve strong prompt-driven zero-...

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