Pulmonology

Exploring the Bone-Vascular Axis: AI-Augmented Chest CT Analysis in COPD Highlights Association Between Vertebral Bone Density and Arterial Calcifications.

OBJECTIVES: Artificial intelligence (AI) tools enable automated assessment of vertebral bone mineral density (BMD), coronary artery calcification (CAC), and aortic calcification on CT scans, offering multimorbidity analysis in chronic obstructive pulmonary disease (COPD) patients. We aimed to investigate the bone-vascular axis with a focus on COPD severity and inhaled corticosteroid (ICS) use. MET...

Predicting 28-day all-cause mortality in critically ill ischemic stroke patients using white blood cell-to-hemoglobin ratio and dual-feature selection machine learning models.

BACKGROUND: The white blood cell-to-hemoglobin ratio (WHR) is a composite biomarker of inflammation and nutrition, but its prognostic role in critically ill ischemic stroke (IS) patients is unclear. METHODS: A cohort of 3,112 patients from MIMIC-IV was analyzed. WHR was calculated from first 24-hour ICU lab values. Its association with 28-day all-cause mortality(ACM) was assessed via survival anal...

Machine learning-based integration of respiratory oscillometry and spirometry for predicting clinical outcomes in spinal muscular atrophy.

UNLABELLED: Assessing respiratory function in spinal muscular atrophy (SMA) is challenging due to the effort-dependent nature of traditional spirometr...

Characterization of telomere-related gene subtypes in lung adenocarcinoma and their implications for prognosis and treatment.

BACKGROUND: Telomeres, located at chromosome ends, regulate cell division and maintain genomic stability. Telomere-related genes (TRGs) play essential...

Ensemble learning-guided discovery of anti-tuberculosis phytochemicals: computational prediction and mechanistic insights.

Tuberculosis (TB) remains a major global health challenge driven by persistent Mycobacterium tuberculosis infection and increasing drug resistance. Ph...

Integrated imaging-informed and machine learning-based prognostic models for risk stratification in connective tissue disease-associated interstitial lung disease: a multicenter study.

OBJECTIVES: Connective tissue disease-associated interstitial lung disease (CTD-ILD) exhibits heterogeneous clinical outcomes, and traditional ILD-GAP...

Natural Language Processing for Automated Classification of Cleft and Craniofacial Procedures From Operative Notes: Model Development and Feasibility Study.

BACKGROUND: The accurate classification of operative notes is essential for surgical outcomes research; however, CPT code classification is notoriousl...

AI-enabled wireless wearable breathing sensor for breathing pattern recognition.

This paper presents an AI-driven multisensor wearable system for real-time breathing pattern recognition by integrating an inertial measurement unit (...

An exploratory study of multi-channel CNN for early detection of lung cancer from longitudinal healthcare records.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with poor survival rates due to late-stage detection. Current low-dose co...

Computational Model for Predicting Optimal Clinical Intervention in Pre-Operative Neonates with Transposition of the Great Arteries.

PURPOSE: Transposition of the Great Arteries (TGA) is a congenital heart defect characterized by the abnormal positioning of the pulmonary artery over...

Construction of a prediction model for depression risk in elderly patients with chronic obstructive pulmonary disease based on machine learning algorithms and analysis of influencing factors.

Patients with chronic obstructive pulmonary disease (COPD) are at a high risk of depression, which not only accelerates disease progression but also s...

VQ-Wave: A Physics-Driven Spatiotemporal Deep Learning Approach for Noncontrast-Enhanced Lung Ventilation and Perfusion MRI.

PURPOSE: To develop a robust deep learning framework for noncontrast-enhanced functional lung MRI, overcoming the limitations of spectral decompositio...

Hyperpolarized 129Xe MRI Features Associated with Interstitial Lung Disease Identified Using an Interpretable Diagnostic Algorithm.

RATIONALE AND OBJECTIVES: Hyperpolarized 129Xe magnetic resonance imaging and spectroscopy (MRI/MRS) have been used to identify numerous imaging and s...

Integrating machine learning and single-cell sequencing to reveal the role of kinase-related genes in subtype classification and prognostic significance of lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) exhibits poor prognosis and a highly complex tumor immune microenvironment (TIME), creating an urgent ...

Zero-TE MRI-based attenuation correction for bone components on chest [18F] FDG PET/MRI: accuracy, repeatability, and external validation of an unsupervised deep learning approach using unpaired PET/CT data.

OBJECTIVE: In positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) for PET of the head is achieved by MRI ...

Predicting atrial fibrillation recurrence after radiofrequency ablation using the AIFV system: a prospective observational study.

BACKGROUND: Pulmonary vein isolation (PVI) has become the cornerstone of atrial fibrillation (AF) treatment. Nevertheless, the efficacy of radiofreque...

Application of multimodal ultrasound radiomics in the diagnosis of superficial lymph node tuberculosis.

OBJECTIVE: To develop preoperative diagnostic models for superficial lymph node tuberculosis (LNTB) using radiomic features extracted from multimodal ...

A Novel Wearables-Based Sleep Quality Index to Quantify Postoperative Sleep Quality.

OBJECTIVE: To develop a novel wearables-based sleep index that can quantify sleep disruption after lung resection and to apply machine learning analys...

Artificial intelligence, omics, and biomarkers: Redefining lung cancer early detection.

Lung cancer, the leading cause of death worldwide, claims millions of lives yearly, largely due to limited early interventions. Currently used lung ca...

From Lumen to Myocardium With Artificial Intelligence: A Clinician's Guide to Comprehensive Cardiac CT.

Coronary artery disease assessment has long focused on stenosis severity, yet luminal narrowing alone fails to capture ischemic burden, plaque vulnera...