Pneumonia

UR$^{2}$-MLLM: Uncertainty-aware Revisit Reasoning in Multimodal Large Language Models for Radiology Report Generation

Radiologists generate diagnostic reports through iterative and selective revisiting of suspicious regions to refine their interpretations. Recent multimodal large language models (MLLMs) for radiology report generation (RRG) have shifted from text-only reasoning toward a ``Thinking-with-Images'' paradigm, incorporating visual evidence into the reasoning process. However, existing methods provide s...

Subgroup performance analysis of adaptation strategies for chest X-ray foundation models

Foundation models are increasingly adapted for downstream medical imaging tasks, yet the influence of the chosen adaptation strategy on subgroup fairness remains poorly understood. We investigate how three parameter-efficient adaptation techniques, including linear heads on the raw CLS token, an MLP, and an attention-pooling module over multi-layer patch features, affect both pathology classificat...

Counterfactual Anatomy-guided Spatial-Temporal Decoding for Annotation-Free Hallucination Mitigation in Medical VLMs

Medical vision-language models (Med-VLMs) have demonstrated strong performance on medical visual question answering, yet they remain prone to hallucin...

FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning

Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We s...

Community Learning Ledgers for Cancer Navigation in Small Island Developing States

Importance. Cancer is the second leading cause of death among patients in the Caribbean, where outcomes are associated with delayed clinical navigatio...

Multi-cohort analysis of 37,739 oral microbiomes reveals ecologically influential health-associated microbial sub-communities across major oral subsites

The oral cavity contains multiple microbial sub-niches, but which taxa consistently play an ecologically important, health-associated role within each...

Analysis of gut bacterial communities leveraging AI methods unveils novel relations between species in Alzheimer's disease

The gut microbiome has been increasingly implicated in Alzheimers disease (AD), with studies reporting numerous species- and genus-level differences. ...

Attention Capture Is Not Detection: A Two-Stage Account of How Humans Miss Localized AI Image Edits

As AI-generated image edits proliferate, the platforms meant to curb the resulting disinformation treat detectability as a single, undifferentiated pr...

Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System

Multimodal Large Language Model (MLLM)-based UAV aerial image understanding and reasoning is essential for aerial intelligence yet poses distinct chal...

RadFusion: Towards Threshold-Controllable Radiology Report Generation

Automated radiology report generation is advancing rapidly in response to the shortage of radiologists, yet unlike a perception model, existing genera...

Linguistically-Aligned and Visually-Grounded Preference Optimization for Clinically-Augmented Medical Report Generation

Despite significant advances in Medical Report Generation (MRG), the reliability remains constrained by the prevalence of factual errors. While Direct...

Regional and Temporal Patterns of COVID-19 Vaccine Misinformation in Sub-Saharan Africa

BackgroundDespite a global rollout of COVID-19 vaccines, Sub-Saharan Africa lagged behind other regions in vaccination coverage, driven primarily by i...

Structure-aware deep learning predicts influenza antigenicity and guides vaccine strain recommendation

The continuous accumulation of genetic mutations in influenza A viruses (IAVs) drives antigenic drift, necessitating precise antigenic prediction for ...

EvtGraph: Event-Adaptive Compression for Sparse Temporal Graph Learning in Multimodal Time Series

Multimodal temporal data are inherently irregular and uneven in information density, yet most models rely on uniform discretization, leading to ineffi...

PDD-RRG: Posterior Diagnostic Decision for Study-level Radiology Report Generation

Automatic radiology report generation (RRG) aims to simulate the workflow of radiologists, assisting them in clinical diagnosis. However, existing met...

HarMoE: Multi-Source Chest Radiograph Pretraining with Dataset-Disentangled Experts

Recent vision-language models for chest X-ray understanding are largely built on image-report alignment and therefore rely heavily on MIMIC-CXR as the...

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer

This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID...

CXR-Retrieve: Compositional Text-to-Image Retrieval in Chest Radiography

Large chest radiography archives are difficult to search because most studies are paired only with free-text reports rather than structured clinical a...

Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data

Automated classification of pulmonary disease from chest radiographs is a widely studied application of machine learning in medical imaging. This pape...

Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification

Cross-modal knowledge distillation can transfer diagnostic knowledge from a strong but costly teacher modality to a cheaper and more deployable studen...