Pulmonology

Machine learning-enabled diagnosis of viral respiratory infections from exhaled volatile organic compound analysis.

Increasing value in the Veterans Affairs Healthcare System (VA) with precision health: a continuing landmark collaboration with the Department of Energy.

OBJECTIVE: Phase II of MVP-CHAMPION, a federal collaboration between the Veterans Affairs Healthcare System (VA) and the Department of Energy (DoE), leveraged large-scale clinical, geo-spatial, and genetic data with state-of-the-art artificial intelligence (AI), and high-performance computing (HPC) to improve value in healthcare. MATERIALS AND METHODS: Eight clinical priority projects for which AI...

Interstitial cation defect chemistry and correlated disorder in melilite solid electrolytes.

Solid electrolytes are fundamental to fuel cells, batteries, sensors and electrolysers. Among them, melilite oxides are promising oxide-ion solid elec...

Prediction of trajectories and outcomes in early-stage metabolic dysfunction-associated steatotic liver disease: a narrative review.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disorder, with manifestations ranging from steato...

Real-Time Evaluation of a Large Language Model for Clinical Practice Guideline Development.

BACKGROUND: The purpose of this study was to evaluate the capability of a large language model (LLM) for performing each of the steps of clinical prac...

AI-Based Denoising for Simulated Dose Reduction in Pediatric Chest Radiography: A Prospective Multicenter Evaluation of Image Quality and Diagnostic Performance.

RATIONALE AND OBJECTIVES: Radiation dose reduction in pediatric chest radiography is a clinical priority due to increased radiosensitivity and cumulat...

Rehospitalization in Preterm Infants: Machine Learning Prediction Model & Associated Risk Factors.

BACKGROUND AND OBJECTIVES: Preterm birth is a major global health concern, with preterm infants (PI) at increased risk of morbidity and rehospitalizat...

Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.

There is considerable interest in training machine learning (ML) models on genomic data that achieve clinical grade diagnostic accuracy. Many successf...

Prediction of the respiratory disease incidence based on environmental factors using machine learning techniques in Penang, Malaysia.

Traditional statistical models often struggle to accurately predict global burden of respiratory diseases due to the complex and interdependent nature...

Identification and validation of biomarkers related to lysine β-hydroxybutyrylation in chronic obstructive pulmonary disease based on transcriptomics data.

Adapting the REVEAL Lite 2 score to the pediatric population through machine learning: insights from the REHIPED registry for pediatric pulmonary hypertension.

INTRODUCTION AND OBJECTIVES: Risk scores for pulmonary hypertension (PH) have been proven useful in adults. However, no risk score has been validated ...

Percutaneous Lung Biopsies Aided by Artificial Intelligence: A Comparison Between Computer and Physician-Chosen Biopsy Paths.

OBJECTIVE: To compare Trajectory Recommendation Algorithm for CT-guided Biopsy (TRAX)-generated lung biopsy puncture pathways versus physician-chosen ...

IL11⁺ fibroblasts are implicated in non-response to anti-TNFα via fibrosis in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is frequently accompanied by intestinal fibrosis, with non-response (NR) to long-term anti-tumor necrosis factor α (a...

Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.

BACKGROUND: Cystic fibrosis related diabetes (CFRD) is a common complication in people with cystic fibrosis (PwCF), yet traditional diagnostic tools s...

Updates on tuberculosis imaging.

Tuberculosis (TB) remains a leading infectious cause of morbidity and mortality worldwide, and major diagnostic and therapeutic challenges persist des...

Machine learning identifies prognosticators of intracranial metastatic disease in patients with breast or lung cancer.

BACKGROUND: Intracranial metastatic disease is a severe complication of cancer that confers substantial morbidity and mortality. Patients with breast ...

Comprehensive analysis of predictive models for disease manifestations and case fatality in systemic lupus erythematosus.

This systematic review evaluated the performance and risk of bias in Systemic Lupus Erythematosus (SLE) disease manifestations and case fatality predi...

Emerging technologies and AI-assisted tools in cardiopulmonary monitoring.

PURPOSE OF REVIEW: Cardiopulmonary monitoring is fundamental to critical care, yet traditional approaches rely on simplified thresholds that capture o...

Biomarkers of mitochondrial dynamics in idiopathic pulmonary fibrosis: Identification and validation through transcriptomic and single-cell analyses.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease that has increasingly been associated with dysregulated mitocho...

Artificial Intelligence in Occupational Health Surveillance: Evaluating AI-Assisted ILO Classification of Radiographs of Pneumoconioses.

BACKGROUND: Pneumoconioses remain an important occupational health issue, particularly in low- and middle-income countries. The International Labour O...