Pulmonology

Incremental prognostic value of immune cell densities beyond clinical parameters in non-small cell lung cancer.

BACKGROUND: Multiplex immunofluorescence imaging enables detailed characterization of the tumor immune microenvironment, but whether immune cell densities add prognostic value beyond established clinical factors in non-small cell lung cancer (NSCLC) remains unclear. METHODS: Tissue samples from an NSCLC cohort (n = 298) were stained with a multiplex immunofluorescence panel targeting immune cell m...

Development and Validation of a Machine Learning Model That Uses Voice to Predict Aspiration Risk.

BACKGROUND: Aspiration causes or aggravates a variety of respiratory diseases. Subjective bedside evaluations of aspiration are limited by poor inter- and intra-rater reliability, while gold standard diagnostic tests for aspiration, such as video fluoroscopic swallow study (VFSS) and fiberoptic endoscopic evaluation of swallowing (FEES), are cumbersome or invasive and healthcare resource intensive...

TabPFN-driven ternary classification of stage IA lung adenocarcinoma subtypes using AI-derived histogram features a retrospective multicenter cohort study.

BACKGROUND: Preoperative differentiation of precursor glandular lesions (PGL), minimally invasive (MIA), and invasive adenocarcinoma (IAC) in stage IA...

Multi-omics Analysis Reveals the Prognostic and Therapeutic Value of TGF-β Signaling-related Genes in Idiopathic Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease with a survival rate comparable to or worse than that of many cancers. Prop...

Lipid nanoparticle-delivered ornithine transcarbamylase mRNA alleviates liver fibrosis in preclinical models.

BACKGROUND AND AIMS: Liver fibrosis poses a major health threat globally, with an acute shortage of effective treatments to stop or reverse its progre...

An Explanation User Interface for Artificial Intelligence-Supported Mechanical Ventilation Optimization for Clinicians: User-Centered Design and Formative Usability Study.

BACKGROUND: The integration of artificial intelligence (AI) into clinical decision support systems (CDSSs) for mechanical ventilation in intensive car...

Detection of Swallowing Abnormalities in Pediatric FEES Recordings Using Rule-Based and Model-Based Methods.

Pediatric swallowing dysfunction (SwD) poses serious health risks, including aspiration, malnutrition, and recurrent respiratory infections, making ea...

Estimating chemical oxygen demand in municipal landfill leachate using multilayer perceptron artificial neural networks based on seasonal monitoring data.

Landfill leachate is a hazardous by-product of municipal solid waste (MSW) and chemical oxygen demand (COD) is a key indicator for evaluating its poll...

Machine Learning Models for Predicting Stroke-Associated Pneumonia: A Systematic Review and Meta-Analysis.

Stroke-associated pneumonia (SAP) is a frequent and severe complication following stroke. Recently, several machine learning (ML) models have been dev...

Reablation of atrial fibrillation targeting electrogram dispersion in patients with isolated veins: The RESTART trial.

BACKGROUND: Pulmonary vein (PV) isolation is a well-established treatment for atrial fibrillation (AF), however, strategies for patients with recurren...

Linking ecological strategies to niche breadth: interpretable machine learning unravels community patterns of nirS-type aerobic denitrifiers along oxygen gradients in drinking water reservoirs.

Aerobic denitrifying bacteria are increasingly recognized for nitrogen removal in deep drinking-water reservoirs, yet how dissolved oxygen (DO) gradie...

Identification of patients at risk for adverse events and poor symptom improvement after transcatheter aortic valve implantation.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) aims to improve symptoms and prognosis, while minimising adverse outcomes. Available predic...

Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects.

Lung cancer is the leading cause of cancer-related deaths globally. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung canc...

Integrative Analysis of Multi-omic Pathways Predict Cancer-Affected Lobes in Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths. The human microbiome plays an important role in regulating response to cancer therapeutics,...

Multiscale Analysis of Deep Learning and Machine Learning: New Insights into the Adsorption Mechanism of VOCs Gas-Sensitive Materials.

Volatile organic compounds (VOCs) associated with lung cancer are key biomarkers for early noninvasive diagnosis, yet their adsorption behaviors on se...

Artificial Intelligence-Assisted Infrared Spectroscopy and Chemometrics for Enhanced Histopathology Screening of Micro- and Macrocancer Lesions.

Accurate detection of micro- and macrocancer lesions remains a critical challenge in histopathology, as conventional hematoxylin and eosin staining re...

A hybrid framework of feature selection and interpretability for dissolved oxygen prediction in drinking water treatment plants.

Accurate prediction of dissolved oxygen (DO) is essential for the sustainable operation of drinking water treatment plants. Conventional approaches of...

Interpretable machine learning unveils non-linear inflammatory thresholds and synergistic interactions in post-burn hypertrophic scarring: development of an intelligent clinical decision support system.

Hypertrophic scarring (HS) following severe burns remains a persistent rehabilitative challenge, yet traditional linear prediction models fail to capt...

Spectroscopic and machine learning approaches for clinical subtyping in systemic sclerosis.

Systemic sclerosis (SSc) is a heterogeneous autoimmune disease characterized by fibrosis, vascular damage, and immune dysregulation. In this study, we...

Explainable multi-modal approach for uncovering key predictors of stroke-risk from ECG, EMG, blood pressure, and respiratory signals.

Accurate and timely stroke-risk prediction is necessary to help patients at risk take guided measures, as stroke remains a leading cause of death and ...