Pulmonology

Pneumonia

Latest AI and machine learning research in pneumonia for healthcare professionals.

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Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)

Current artificial intelligence models for medical imaging are predominantly single modality and s...

AdFair-CLIP: Adversarial Fair Contrastive Language-Image Pre-training for Chest X-rays

Contrastive Language-Image Pre-training (CLIP) models have demonstrated superior performance acros...

Community-Based Efficient Algorithms for User-Driven Competitive Influence Maximization in Social Networks

Nowadays, people in the modern world communicate with their friends, relatives, and colleagues thr...

FedCLAM: Client Adaptive Momentum with Foreground Intensity Matching for Federated Medical Image Segmentation

Federated learning is a decentralized training approach that keeps data under stakeholder control ...

Causal Representation Learning with Observational Grouping for CXR Classification

Identifiable causal representation learning seeks to uncover the true causal relationships underly...

Multimodal Large Language Models for Medical Report Generation via Customized Prompt Tuning

Medical report generation from imaging data remains a challenging task in clinical practice. While...

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor

In AI research and practice, rigor remains largely understood in terms of methodological rigor -- ...

Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models

Counterfactual image generation aims to simulate realistic visual outcomes under specific causal i...

RadFabric: Agentic AI System with Reasoning Capability for Radiology

Chest X ray (CXR) imaging remains a critical diagnostic tool for thoracic conditions, but current ...

Beyond the First Read: AI-Assisted Perceptual Error Detection in Chest Radiography Accounting for Interobserver Variability

Chest radiography is widely used in diagnostic imaging. However, perceptual errors -- especially o...

Beyond True or False: Retrieval-Augmented Hierarchical Analysis of Nuanced Claims

Claims made by individuals or entities are oftentimes nuanced and cannot be clearly labeled as ent...

Anatomy-Grounded Weakly Supervised Prompt Tuning for Chest X-ray Latent Diffusion Models

Latent Diffusion Models have shown remarkable results in text-guided image synthesis in recent yea...

CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray

The CXR-LT series is a community-driven initiative designed to enhance lung disease classification...

A Narrative Review on Large AI Models in Lung Cancer Screening, Diagnosis, and Treatment Planning

Lung cancer remains one of the most prevalent and fatal diseases worldwide, demanding accurate and...

A Comprehensive Analysis of COVID-19 Detection Using Bangladeshi Data and Explainable AI

COVID-19 is a rapidly spreading and highly infectious virus which has triggered a global pandemic,...

Parking, Perception, and Retail: Street-Level Determinants of Community Vitality in Harbin

The commercial vitality of community-scale streets in Chinese cities is shaped by complex interact...

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification

Purpose: This study proposes a framework for fine-tuning large language models (LLMs) with differe...

Revolutionizing Radiology Workflow with Factual and Efficient CXR Report Generation

The escalating demand for medical image interpretation underscores the critical need for advanced ...

An anatomically enhanced and clinically validated framework for lung abnormality classification using deep features and KL divergence.

Detecting lung abnormalities via chest X-rays is challenging due to understated tissue variations of...

Jun 2025 40488166
Detection of COVID-19, lung opacity, and viral pneumonia via X-ray using machine learning and deep learning.

The COVID-19 pandemic has significantly strained healthcare systems, highlighting the need for early...

Jun 2025 40198984
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