COPD

Gene expression and metadata based identification of key genes for lung cancer, COPD, and IPF using machine learning and statistical models.

Lung cancer (LC) is one of the most prevalent and deadly cancers globally, presenting a major public health challenge. Patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are at a significantly higher risk of developing lung cancer. Despite developments in research, the primary molecular pathways of many disorders remain poorly understood. The current...

Signs and symptoms indicating the transition to the palliative phase in patients with COPD and heart failure in primary healthcare: a mixed-methods study.

Identification of key influencing factors of health information literacy in COPD patients: a cross-sectional study using a random forest model.

The Montafon proposal: New insights and emerging concepts in pulmonary rehabilitation.

Background Pulmonary rehabilitation (PR) is beneficial, yet outcome assessment remains inconsistent. A multidisciplinary D-A-CH working group reviewed...

Plasma proteomic profiling with machine learning identifies immunometabolic perturbations associated with smoking and smoking cessation.

Cigarette smoking is the leading modifiable risk factor for chronic obstructive pulmonary disease (COPD) and is associated with systemic molecular alt...

Current and future contributions of AI to pulmonary function test interpretation, diagnostic approaches, and predictions of disease progression.

INTRODUCTION: Artificial intelligence (AI) methods - including machine learning, deep learning, and explainable AI - are increasingly applied to pulmo...

Exploring approaches to computational representation and classification of user-generated meal logs.

OBJECTIVE: This study examined the use of machine learning (ML) and domain-specific enrichment in patient-generated health data, in the form of free-t...

A review of artificial intelligence-based research on chronic obstructive pulmonary disease.

In recent years, with the rapid development of artificial intelligence (AI), Chronic Obstructive Pulmonary Disease (COPD), one of the world's three ma...

Unsupervised identification of muscle phenotypes in adults with obesity: a data-driven framework for the identification of sarcopenia in absence of a gold standard.

BACKGROUND: Sarcopenia is characterized by progressive loss of skeletal muscle mass and strength and is associated with increased disability and morta...

Assessing the influence of kernel selection on chest computed tomography image quality across varying dose levels using TrueFidelity reconstruction.

Deep learning image reconstruction (DLIR) utilizes neural networks to generate high-quality computed tomography (CT) images. One commercially availabl...

Machine learning-driven optimization of monolithic gold plasmonic sensors: Achieving ultrahigh sensitivity with interpretable linear models.

Integrating machine learning (ML) with nanophotonic engineering, this work achieves unprecedented performance in surface plasmon resonance (SPR) biose...

Deep Learning-Based Estimated Pulmonary Biological Age From Chest Computed Tomography Images in Healthy Adults: Model Development and Validation Study.

BACKGROUND: Estimated pulmonary biological age (ePBA) has emerged as a more reliable indicator for disease progression and mortality than chronologica...

Definitions of early COPD and predictors for disease progression: a systematic review.

INTRODUCTION: Early chronic obstructive pulmonary disease (COPD) is considered to represent the initial phase of the disease. However, inconsistent te...

Explainable artificial intelligence-enhanced dual-mode electrochemical sensor for online monitoring of dimethoate.

Electrochemical impedance spectroscopy (EIS) uses small alternating-current perturbations to probe charge-transfer and mass-transport processes across...

Comparison of monocular video-based methods for measuring the amplitude of hand tremor.

Accurate assessment of hand tremor is critical to help diagnose and monitor multiple neurological conditions. In routine practice, clinicians subjecti...

CT image-based machine learning models for predicting blood eosinophil levels in acute exacerbation of chronic obstructive pulmonary disease.

Artificial Intelligence Models for Predicting Triage in Emergency Departments: Seven-Month Retrospective Comparative Study of Natural Language Processing, Large Language Model, and Joint Embedding Predictive Architectures.

BACKGROUND: Triage errors in emergency departments (EDs), including undertriage and overtriage, pose significant risks to patient safety and resource ...

GOLD 2026: Transforming COPD Management with Early Intervention, Multi-dimensional Assessment, and Personalized Care.

The 2026 report from the Global Initiative for Chronic Obstructive Lung Disease (GOLD) introduces substantial conceptual and practical updates to the ...

Similarity of sputum mediator signatures between e-cigarette users and COPD depends on GOLD stage and type of e-cigarette: a pilot study.

There is overlap in symptoms and airway pathobiology between COPD and e-cigarette (e-cig) users. We sought to determine if young adult e-cig users hav...

Precise oxygen therapy to emphysema patients by fuzzy-based gain tuning control of set-point regulated MRAC.

Emphysema, a primary component of chronic obstructive pulmonary disease (COPD), causes progressive dyspnea through the destruction of alveolar membran...