COVID-19

Macrophage signature-based prediction of cancer treatment response using MIL-attention

Predicting immunotherapy response from single-cell data remains difficult due to patient-level labels, extreme class imbalance, and highly heterogeneous macrophage states. We present a Multiple Instance Learning (MIL) framework that treats each patient as a bag of macrophage embeddings derived from a single-cell RNA foundation model. The architecture incorporates an attention-based pooling mechani...

RARF: Region-Aware Rectified Flows for 3D Brain MRI Inpainting

Medical image inpainting has the potential to improve automated brain MRI analysis by reconstructing healthy tissue within pathological regions. We introduce RARF, a task-agnostic region-aware rectified flow framework for masked data generation. We instantiate the framework for 3D brain MRI inpainting as our submission to the BraTS Inpainting Challenge 2026. RARF restricts the stochastic interpola...

BooM-VVT: Boosting Mask-Free Video Virtual Try-On with Image-Level Pseudo Data

Video virtual try-on (VVT) aims to generate realistic videos of a person wearing a target garment. Recent methods leverage a keyframe-driven video gen...

Exemplar: Classical Priors Complement Frozen Features for Few-Shot Microscopy Segmentation at Native Resolution

Segmenting a new biomedical dataset usually means a domain-specific model trained on substantial annotation, or a foundation model steered at inferenc...

InfraPatch: Cross-Task Targeted Grayscale Patch Attacks on Infrared-Adapted Vision-Language Models

Infrared vision-language models (IR-VLMs) have emerged as a promising paradigm for multimodal perception under low-visibility conditions, yet their ro...

CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning

Semantic triggers in federated learning (FL) can be less conspicuous than synthetic patches, but sample-dependent placement may weaken backdoor implan...

Swin Meets EfficientNet: Lightweight Architectures for GAN-Based Face Forensics

Modern generative models, such as GANs, diffusion architectures, and autoregressive systems, now produce facial images that are nearly indistinguishab...

MROP: Mask-Region Optimized Purification Against Backdoor Attack in Deep JSCC

Deep joint source and channel coding (JSCC) transmits a source by mapping it directly to channel symbols through an end-to-end deep neural network (DN...

PredErase: Training-Free Object-and-Effect Removal with Predictive Latent Guidance

Removing an object is not the same as filling its mask. Cast shadows and contact shading usually lie outside the user-provided instance mask M_obj, so...

Expert-like Bone Ultrasound Segmentation through Expert-in-the-loop Mask-conditioned Progressive Learning

Manual annotation remains a major bottleneck in ultrasound (US) bone segmentation, where experts typically iteratively refine rough brush masks rather...

A data-driven regional amyloid PET score predicts cognitive decline beyond Centiloid

Background: The Centiloid (CL) scale standardizes global amyloid PET quantification and is widely used to define amyloid positivity. As a global summa...

Audited vibe coding suggests partial fetal-like convergence of tumor proteomes

The balance between how much human tumors recapitulate fetal tissue programs versus lose adult tissue identity remains unresolved. I used audited vibe...

Beyond Accuracy: Quantifying Pulmonary Attribution in Anatomy-Guided Chest X-Ray Classification Under Domain Shift

Deep-learning models can achieve strong chest X-ray (CXR) classification performance without establishing whether their predictions predominantly rely...

Segmentation of Bovid Dentition Under Imperfect Annotations: A Comparative Study of Convolutional and Attention Models

Semantic segmentation decomposes an image into distinct mask regions corresponding to different object categories, such as people, cars, signs or buil...

Learning Human Health and Diseases from 24-hour Wrist Movement

Much of human health and function unfolds beyond the clinic, through the movements of everyday life. Wrist-worn accelerometers capture these movements...

Discrete Diffusion Bridges for Spatiotemporally Aligned Image Translation and Generation

We propose Discrete Diffusion Bridges (DDB), a novel framework designed to resolve the fundamental spatiotemporal misalignment of standard discrete di...

CIViC-Fact: a proof-of-concept framework for AI-assisted verification of cancer variant interpretations

Accurate interpretation of genomic variants is critical for precision oncology but remains slow and dependent on specialized expertise. Public knowled...

ARC-CT: Anatomy-Routed Contrastive Vision-Language Learning for 3D Chest CT

Contrastive vision-language learning uses paired chest CT volumes and radiology reports to learn abnormality classifiers without manually annotated la...

Advancing Interaction-Sensitive Feature Selection: Novel Relief-Based Algorithms, Expanded Comparisons, and Recommendations for Biomedical Data Mining

As a precursor to high-dimensional biomedical data modeling, reliable feature selection can reduce computational expense, improve modeling performance...

Beyond Padua and IMPROVE: Machine Learning Outperforms Guideline Risk Scores for Prediction of Radiologically Confirmed Hospital-Acquired Venous Thromboembolism

*Background:** Hospital-acquired venous thromboembolism (VTE) is a leading preventable cause of in-hospital morbidity and mortality. Guideline-endorse...