Pulmonology

Interpretable machine learning model for predicting the risk of dysphagia in patients after cardiac surgery.

BACKGROUND: Dysphagia is recognized as one of the most common severe complications following cardiac...

Feasibility of Implicit Neural Representation Learned Motion Compensation for 3D Stack-of-Spirals Free-Breathing Cardiac Quantitative Susceptibility Mapping.

PURPOSE: Differential blood oxygenation between the right and left heart (ΔSO2) is an indicator of c...

Sustainable Strategies in Tuberculosis Management: Bridging Ethnobotanical Pharmacology, Advanced Drug Delivery, and AI-Driven Innovation.

Tuberculosis (TB) persists as a leading infectious disease, with progress in global control complica...

Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases.

Over the past decade, Investigative Radiology has published numerous studies that have fundamentally...

Lung-DDPM: Semantic Layout-Guided Diffusion Models for Thoracic CT Image Synthesis.

With the rapid development of artificial intelligence (AI), AI-assisted medical imaging analysis dem...

Quantitative Chest Computed Tomography and Machine Learning for Subphenotyping Small Airways Disease in Long COVID.

PURPOSE: To investigate imaging phenotypes in posthospitalized COVID-19 patients by integrating quan...

Leveraging Artificial Intelligence to Transform Thoracic Radiology for Lung Nodules and Lung Cancer: Applications, Challenges, and Future Directions.

This review traces the historical path of artificial intelligence (AI) methods that have been applie...

Quantitative CT and Artificial Intelligence in Chronic Lung Disease.

Computed tomography (CT) is routinely used in diagnosing and managing patients with chronic lung dis...

Retrieval Augmented Generation (RAG) for Evaluating Regulatory Compliance of Drug Information and Clinical Trial Protocols.

The purpose was to evaluate retrieval-augmented generative (RAG) artificial intelligence (AI) method...

A Self-Supervised Foundation Model Based on Three-Dimensional Chest CT Scans for Lung Cancer Diagnosis and Prognosis Prediction.

Purpose To develop a self-supervised chest CT foundation model and evaluate its performance in lung ...

Simultaneous synthesis of perfusion and ventilation images from CT using a dual-decoder residual attention network for lung disease diagnosis.

BACKGROUND: Deep learning algorithms can synthesize pulmonary functional images from CT images. Howe...

Image quality restoration in 15-s breath-hold PET using a diffusion-based neural network.

BACKGROUND: Breath-hold PET imaging helps reduce respiratory motion artifacts in thoracoabdominal sc...

Multidimensional cfRNA response modeling identifies a 5-gene pair signature for high-robust pulmonary tuberculosis diagnosis.

Lack of non-invasive biomarkers hinders pulmonary tuberculosis (PTB) management. We developed a mult...

An interpretable molecular descriptor for machine learning predictions in atmospheric science.

The study of aerosol formation and chemistry using machine learning is limited by the lack of molecu...

Targeted inhibition of RGS19 alleviates renal fibrosis by restoring autophagy and modulating immune cell infiltration.

Renal fibrosis, a progressive pathological feature of chronic kidney disease (CKD), is driven by imp...

Machine Learning-Informed Nano Co-Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue.

Nanoparticle-based drug delivery faces persistent challenges, including complex fabrication processe...

The regional landscape of the human colon culturome in health and cystic fibrosis.

UNLABELLED: Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities acro...

Identification of key clinical features for pediatric respiratory syncytial virus infection using machine learning.

Fcer1g and St3gal1: Macrophage-associated angiogenesis biomarkers and therapeutic targets in sepsis-induced acute lung injury.

BACKGROUND: Acute lung injury (ALI) involves the release of growth factors and inflammatory mediator...

Distinguishing post-COVID from long-COVID in adults: Development and validation of a biomarker signature using targeted proteomics and machine learning in a cross-sectional observational study.

BACKGROUND: COVID-19 can have diverse clinical manifestations, ranging from asymptomatic infection t...

Integrated machine learning risk model for predicting radiation pneumonitis in lung cancer patients with interstitial lung disease.

BACKGROUND: Radiation pneumonitis (RP) is a serious complication in lung cancer patients with pre-ex...