Pulmonology

Multicentre MRI-based machine learning model for noninvasive prediction of pulmonary metastasis in osteosarcoma integrating intra-tumoral heterogeneity features.

OBJECTIVES: To develop and externally validate a multicenter MRI-based machine learning model integrating intra-tumoral heterogeneity (ITH) index, conventional radiomics (C-radiomics) and clinical variables for predicting one-year pulmonary metastasis (PM) in osteosarcoma. MATERIALS AND METHODS: This retrospective study enrolled 320 patients with histologically confirmed osteosarcoma from four ins...

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 analysis to these indices to identify patients exhibiting distinct postoperative sleep patterns. METHODS: This prospective observational cohort study analyzed patients undergoing lung resection who wore wearable devices preoperatively and at least 90-days ...

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...

Inspiratory muscle training devices for chronic lung disease management: current evidence and future directions.

INTRODUCTION: Inspiratory muscle training (IMT) is a potential adjunct therapy to improve inspiratory muscle strength and endurance, exercise capacity...

Heterojunction-Engineered Mass Spectrometry Platform for Deciphering Serum Metabolic Fingerprints in Diagnosis of Respiratory Diseases.

Respiratory diseases, including bronchial asthma (BA), chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), and lung cancer ...

Development and external validation of an interpretable machine-learning model for HFpEF comorbidity risk in COPD patients.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) and Heart Failure with preserved Ejection Fraction (HFpEF) frequently coexist, leading to inc...

Validation of a machine learning model for predicting early deterioration in the emergency department.

Early recognition of patients at risk for deterioration in the emergency department (ED) is critical for patient safety. Traditional early warning sco...

Metabolomics and Artificial Intelligence (AI) assisted metabolomics in the diagnosis of non-tuberculous mycobacterial infections: progress and challenges.

BACKGROUND: Non tuberculous mycobacterial (NTM) infections are caused in individuals who are immunocompromised or with certain lung conditions. The NT...

Emerging Therapeutic Paradigms in Tuberculosis: Nanocarriers, Host-Directed Strategies, and Translational Pharmacology.

TB remains a significant global health burden due to protracted therapeutic courses, poor patient compliance, and toxicities associated with drug trea...

Multiple Targets and Pathways Non-Monotonically Regulate Lung Squamous Cell Carcinoma Migration in Response to Phthalates.

Phthalates (PAEs) are widely used plasticizers that are increasingly linked to tumorigenesis. In this study, we integrated network toxicology and mach...

Machine learning reveals proteome-encoded growth determinants underlying metabolic versatility of Rhodopseudomonas palustris on lignin-derived aromatics.

Lignin depolymerization generates mixtures of aromatic compounds that are promising carbon sources for microbial bioconversion, yet the constraints go...

Machine Learning-Based Prediction Model for Infectious Complications in Trauma and Its Association With In-Hospital Mortality.

BACKGROUND: Infectious complications, such as sepsis or catheter-related infections, are common and serious sequelae after trauma. Despite their clini...

Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.

OBJECTIVE: To provide a structured narrative review of current evidence and future directions for artificial intelligence (AI) applications in the ter...

A temporal deep learning algorithm for prediction of extubation failures in critical care patients.

Extubation failure in ICU patients is associated with poor outcomes. Existing prediction models often rely on static data, missing dynamic disease flu...

Breaking Atomic Fe-N4 Symmetry in Aerogel Catalysts by Nitrogen and Chlorine Doping for Enhancing Oxygen Reduction.

The growing demand for metal-air batteries and fuel cells has spurred extensive research into low-cost, highly efficient, noble-metal-free electrocata...

Cough Audio Recognition for Early Detection of Respiratory Diseases: Algorithm Development and Validation Study.

BACKGROUND: Coughing is a common clinical symptom and a protective respiratory reflex closely associated with various respiratory system diseases. The...

Spermidine suppresses liver fibrosis by remodeling the communication signal between liver sinusoidal endothelial cells and hepatic stellate cells.

Hepatic fibrosis is a pivotal stage in which chronic liver disease progresses from reversible injury to decompensation. Liver sinusoidal endothelial c...

Commercial AI for CT lung cancer screening: product capabilities, coverage of nodule management tasks and supporting evidence.

OBJECTIVES: To characterize the capabilities of CE-marked AI products for lung nodule analysis in lung cancer screening (LCS), quantify their coverage...

Machine learning and SHAP-based risk assessment of PICC-related bloodstream infections in premature infants at the time of clinical suspicion.

BACKGROUND: Peripherally inserted central catheter-related bloodstream infections (PICC-CRBSI) pose a serious threat to preterm infants. This study ai...