Pulmonology

Viral pneumonia detection during the COVID-19 pandemic using deep learning and DCGAN-based data augmentation.

Deep learning has shown strong potential for automated chest X-ray analysis in the diagnosis of respiratory diseases. However, accurate detection of viral pneumonia remains challenging due to its radiographic similarity with COVID-19 and limited labeled data. In this study, we aim to detect viral pneumonia in chest X-ray images using CNNs, MobileNet, and an ensemble approach, with DCGAN-based data...

Use of machine learning and voice for multiclass classification of Parkinson's disease, chronic obstructive pulmonary disease, and healthy controls.

Parkinson's disease (PD) and chronic obstructive pulmonary disease (COPD) are prevalent conditions with substantial impact on quality of life and health care systems. Both disorders affect voice production through different physiological mechanisms, yet neither condition has a widely adopted objective biomarker for routine clinical use. Voice analysis has emerged as a non-invasive digital biomarke...

Real-time prediction of cardiorespiratory deterioration during paediatric critical care transport using interpretable machine learning.

Interhospital transport of critically ill children carries inherent risks, including unexpected respiratory and cardiovascular deterioration. Early wa...

Evaluating expert opinions on using a virtual patient app based on artificial intelligence for teaching brief smoking cessation advice to medical students: a cross-sectional study.

BACKGROUND: Smoking is one of the main preventable causes of premature disease and death. Anti-smoking counseling continues to be a challenge to cover...

Application of artificial intelligence-assisted education for postoperative pulmonary rehabilitation: a hybrid model of AI and nurse-driven support.

OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cance...

Air pollution-related health impacts from domestic waste burning and associated interventions: the merits of a traditional versus machine learning scoping review methodology.

Regularly updating repositories of air pollution impacts on health is essential for evidence-based policies, interventions, and progress monitoring. H...

Single-cell profiling and machine learning identify cuproptosis-related fibroblast subpopulations and fibrogenesis modulator AEBP1 in endometriosis.

Endometriosis is characterized by progressive fibrosis and limited therapeutic options. Cuproptosis, a copper-dependent form of regulated cell death, ...

Global whole-genome, phylodynamic, and machine-learning analysis of Glaesserella parasuis serovars 2, 5, and 12.

Glaesserella parasuis is a respiratory pathogen of swine and the causative agent of Glässer's disease. Among the 15 serotypes, serotypes 2, 5, and 12 ...

Explainable machine learning incorporating CHI3L1 enhances liver fibrosis staging in chronic hepatitis B: The CHILI multicenter study.

BACKGROUND: Identifying significant liver fibrosis (≥F2) is critical for initiating antiviral therapy in chronic hepatitis B (CHB). Chitinase-3-like p...

Large-scale cryptic proteome mining revealed potential phage-mediated host-pathogen genetic exchange in Mycobacterium tuberculosis.

BACKGROUND: Due to inevitable evolution, clinical strains of Mycobacterium tuberculosis (Mtb) exhibit distinct phenotypes and differ significantly fro...

Early Risk Stratification for Mechanical Ventilation in Acute Ischemic Stroke: Development and Validation of a Simplified Clinical Score.

Background and PurposeMechanical ventilation (MV) occurs in a substantial subset of acute ischemic stroke (AIS) hospitalizations and is associated wit...

Prediction Model for Delirium in Patients with Sepsis-Associated Liver Injury: An Interpretable Machine Learning Approach.

BackgroundPatients with sepsis-associated liver injury (SALI) are at marked risk of delirium, a severe complication strongly linked with poor neurolog...

Early laboratory-based differentiation of severe influenza pneumonia and influenza-associated encephalopathy in children using a multi-model, stability-aware machine-learning workflow: a single-center retrospective cohort study.

BACKGROUND: Influenza-associated encephalopathy and acute necrotizing encephalopathy (ANE) are rare but devastating complications of pediatric influen...

MTRFU-Net: a lung nodule segmentation model based on improved U-Net architecture with spatial-frequency fusion.

Accurate pulmonary nodule segmentation is a key step for the early diagnosis of lung cancer, yet existing deep learning methods still have limitations...

cGAS-STING pathway regulated by spatiotemporal heterogeneity of tumor microenvironment and precision therapy strategies in lung cancer.

The cGAS-STING pathway is a central regulator of innate immunity and exhibits a complex dual function in lung cancer: it can activate anti-tumor immun...

Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis.

PURPOSE: Silicosis, the most dangerous and common lung illness associated with breathing in mineral dust, is a significant health concern. Although Re...

Single-cell and spatial analyses identify a glycolysis-high state driven by STOML2 in epithelial ovarian cancer.

OBJECTIVE: Metabolic heterogeneity contributes to therapeutic resistance and poor prognosis in epithelial ovarian cancer (EOC), yet the regulatory dri...

The role of whole genome sequencing in antimicrobial susceptibility prediction of bacteria: 2025 update from the EUCAST Subcommittee.

SCOPE: The 2017 European Committee on Antimicrobial Susceptibility Testing (EUCAST) subcommittee report on the role of Whole Genome Sequencing (WGS) i...

Integrated Diagnosis of Submassive Pulmonary Embolism Using Computed Tomography Angiography, Echocardiography, and Artificial Intelligence.

OBJECTIVES: Early intervention in submassive pulmonary embolism (SMPE) has been shown to improve long-term cardiopulmonary outcomes compared to antico...

Role of Low-Field Magnetic Resonance Imaging in the Lungs: Opportunities and Challenges.

Clinical utilization of lung MRI has not kept pace with MRI of other body regions. This is due to a combination of technical and perceptual factors re...