Pulmonology

Prognostic significance of right ventricular myocardial features derived from echocardiography using a deep learning framework in pulmonary arterial hypertension.

BACKGROUND: The function and myocardial characteristics of the right ventricle (RV) are linked to RV dysfunction and prognosis in pulmonary arterial hypertension (PAH). The prognostic value of RV myocardial features derived from echocardiography remains unclear. METHODS: A total of 166 patients (mean age, 35.6±11.7 years; 133 females) were included. The primary endpoint was a composite of cardiova...

Artificial intelligence-assisted peri-operative echocardiography: a multicentre observational study.

INTRODUCTION: Point-of-care transthoracic echocardiography performed by anaesthetists can influence peri-operative management but is constrained by time, the need for measurements and advanced skill requirements. Artificial intelligence-driven analysis may streamline this assessment and yield benefits to clinicians and patients. METHODS: In this prospective multicentre observational study, adult p...

Comprehensive evaluation of cross cancer generalization in histopathology segmentation models across 21 tumor types.

BACKGROUND: Artificial intelligence has significantly advanced computational pathology by enabling high-resolution, clinical-grade tumor segmentation ...

Deep learning model development and clinical validation for radiographic surrogate markers of implant esthetic risk.

Reliable risk assessment for implant-supported restorations in the esthetic zone is critical yet challenging due to complex anatomical variations and ...

The Application of Machine Learning in the Development of Co-Amorphous Dry Powder Inhalation.

Besides improving drug solubility and stability, co-amorphous systems (COAMS) have recently been reported to enhance the pulmonary delivery efficiency...

Machine learning-based prediction of ventilator therapeutic pressure for optimized CPAP titration.

BACKGROUND: Accurate prediction of therapeutic pressure for Continuous Positive Airway Pressure (CPAP) therapy is essential for effective treatment of...

Early identification of high-risk individuals for mortality after lung transplantation: A retrospective cohort study with topological feature engineering.

Lung transplantation remains the only definitive treatment for end-stage respiratory failure; however, it has substantial post-operative mortality ris...

Identifying factors associated with vaping cessation in young adults: A machine learning and XAI approach.

The public health impact of vaping in the United States reflects a complex balance of potential benefits and emerging risks, as e‑cigarettes may reduc...

AIBAN-AI Bronchial Detection and Airway Navigation System.

BACKGROUND: Accurate navigation within the lungs is critical for bronchoscopy procedures but remains challenging due to the complex airway anatomy. Ar...

Neutrophil extracellular traps-related biomarkers in idiopathic pulmonary arterial hypertension: A machine learning-based identification and experimental validation study.

Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular m...

Development and validation of a risk stratification model for sarcopenia in patients with chronic lung disease: a cross-sectional study based on CHARLS data.

OBJECTIVE: The aim of this study was to develop a machine learning-based stratification model to identify high-risk individuals for sarcopenia among p...

Supervised Learning for Collagen Segmentation in Bright-Field Histology: A Comparative Evaluation of U-Net and MLP.

PURPOSE: Quantifying collagen in histological slides is essential for diagnosing and monitoring fibrosis. However, the combination of PicroSirius Red ...

Cost-effectiveness of latent tuberculosis infection screening using interferon-gamma release assays among migrants to Japan: a Markov modelling study incorporating social vulnerability and access barriers.

OBJECTIVE: This study aims to evaluate the cost-effectiveness of latent tuberculosis infection (LTBI) screening strategies using interferon-gamma rele...

Understanding LUng Cancer risk factors and their Impact Assessment (LUCIA): protocol for multicentre observational cohort study.

INTRODUCTION: Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, primarily due to diagnosis at advanced stages. Although low...

Classification of spinal tuberculous infection, pyogenic infection and spinal metastasis from magnetic resonance imaging using machine learning.

BACKGROUND: Differentiating between spinal tuberculosis, pyogenic (bacterial) spondylitis and spinal metastasis remains a major diagnostic challenge b...

Development and evaluation of an ontology for non-invasive respiratory support in acute care.

Managing patients with respiratory failure increasingly involves non-invasive respiratory support (NIRS) strategies to support respiration, often prev...

Development of a four-gene host signature for paucibacillary TB among symptomatic individuals with sputum Xpert MTB/RIF Ultra very low and trace results.

OBJECTIVES: The Xpert MTB/RIF Ultra (Ultra) assay is widely used to diagnose pulmonary tuberculosis (TB), but "very low" or "trace" results may reflec...

Comprehensive Multi-Omics Profiling of Tertiary Lymphoid Structures Reveals Immunogenetic Landscapes and Prognostic Subtypes in Lung Adenocarcinoma.

Tertiary lymphoid structures (TLSs) are key components of the tumor immune microenvironment and show prognostic relevance in many cancers. However, th...

From Genomic Instability to Epigenetic Signatures: The Evolving Landscape of Circulating Cell-free DNA in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a leading global health burden, yet its diagnosis and staging rely heavily...

Identification of Mitochondrial Dysfunction Genes as Diagnostic Biomarkers for Ischemic Stroke by Integrated Bioinformatics Analysis and Machine Learning.

Current diagnostics for ischemic stroke (IS) lack timeliness and accessibility, highlighting the need for novel molecular diagnostic models. Three gen...