COPD

Predictive design of stretchable electrodes with strain-insensitive performance via robotics- and machine learning-integrated workflow.

Innovations in wearable electronics and soft robotics hinge significantly on the development of stretchable electrodes. However, a persistent challenge lies in balancing high stretchability, functional performance, and strain insensitivity. Conventional approaches, such as design of experiments and trial-and-error methods, often rely on time-consuming and labor-intensive experiments to navigate a ...

Integrating multi-omics and machine learning systematically deciphers cellular heterogeneity and fibrotic regulatory networks in the progression from MASLD to MASH.

The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic dysfunction-associated steatohepatitis (MASH) is a critical link leading to cirrhosis and hepatocellular carcinoma. Yet the responsible cellular programs remain unclear. We integrated public single-cell, spatial, and bulk transcriptomic datasets to map microenvironmental remodeling and regulatory net...

Machine Learning Predictive Models for Prognosis in Patients undergoing Endovascular Abdominal Aortic Aneurysm Repair.

BACKGROUND: An increasing number of patients with abdominal aortic aneurysms (AAAs) are opting for endovascular aneurysm repair (EVAR), and predicting...

Single-inspiratory quantitative CT nomogram for enhanced PRISm and COPD differentiation: a cross-sectional study with interpretable diagnostic boundaries.

BACKGROUND: Differentiating preserved ratio impaired spirometry (PRISm) from chronic obstructive pulmonary disease (COPD) is challenging. Traditional ...

Recent advances in gold and zinc oxide nanoparticles: Antibiofilm action, mechanisms beyond ROS generation, and in vivo efficacy.

Gold (Au) and zinc oxide (ZnO) nanoparticles (AuNPs/ZnONPs, respectively) are well-established antimicrobial nanomaterials with broad-spectrum activit...

Prediction of the Preclinical Stage of Coal Workers' Pneumoconiosis on Nonimaging Data Integrating Prior Knowledge and Machine Learning.

OBJECTIVE: This study aims to establish machine learning models using nonimaging data from health examinations of coal workers, which can screen the p...

Artificial intelligence in lymphedema: A systematic review of diagnostic and clinical applications.

BACKGROUND: Lymphedema is a chronic, progressive condition characterized by impaired lymphatic drainage and fluid accumulation. Conventional diagnosti...

Hitting the Bull's AI: Artificial Intelligence-derived Imaging Features and their Association with Outcomes in CT-guided Lung Biopsy, a Retrospective Study.

PURPOSE: This study aims to evaluate whether quantitative imaging features analyzed by an artificial intelligence (AI) tool are associated with succes...

Radiologist- and computer-based chest imaging quantification at 12 months post transplant correlates with baseline lung allograft dysfunction.

BACKGROUND: Baseline lung allograft dysfunction (BLAD), defined as failure to achieve ≥ 80% predicted spirometry after lung transplant, is associated ...

Label-free gold nanostar-based SERS with machine learning: A platform for detecting endometrial cancer-associated polyamine metabolites.

The occurrence and progression of endometrial cancer are closely associated with metabolic reprogramming, in which polyamine metabolites play a critic...

Construction and validation of a machine learning-based risk prediction model for invasive mechanical ventilation in AECOPD patients complicated with respiratory failure.

OBJECTIVE: This study aimed to create and validate a machine learning (ML) model to predict the likelihood of invasive mechanical ventilation (IMV) in...

Understanding and Addressing Bias in Artificial Intelligence Systems: A Primer for the Emergency Medicine Physician.

Artificial intelligence (AI) tools and technologies are increasingly being integrated into emergency medicine (EM) practice, not only offering potenti...

Pediatric asthma management via integration of a remote spirometry device into an EHR-based artificial intelligence-powered clinical decision support system: A feasibility pragmatic clinical trial.

BACKGROUND: Asthma is the most common chronic disease in children. Suboptimal asthma control is prevalent and causes significant health care costs. El...

Clinical decision support system for detecting right ventricular dysfunction in acute pulmonary embolism: Explainable a new Binary Rule Search (BRS) ensembles and robustness evaluation.

BACKGROUND: Right-ventricular dysfunction (RVD) in acute pulmonary embolism (PE) carries excess short-term mortality; fast, transparent risk stratific...

Comment on "Medication-based mortality prediction in COPD using machine learning and conventional statistical methods".

[Neck dissection-more, less, targeted?].

Neck dissection is an essential part of surgical treatment for head and neck malignancies. In recent years, the extent of neck dissection required for...

Automated lung sound detection via Bi-GRU-modified SqueezeNet architecture with new stock well feature set.

Lung sound analysis is critical for diagnosing respiratory diseases such as asthma, bronchiectasis, bronchiolitis, COPD, LRTI, pneumonia, and URTI. Tr...

Quantitative CT of emphysema, wall thickness and mucus plugs in alpha-1-antitrypsin deficiency: relationship to clinical outcomes.

OBJECTIVES: Alpha-1-antitrypsin deficiency (AATD) is a rare genetic disorder leading to chronic obstructive pulmonary disease (COPD). Emphysema is the...

Single-step extraction & plasmonic sensing of sulphur in fuels using machine learning analysis of RGB images.

BACKGROUND: Mercaptans are compounds of great concern because they are one of the main sources of sulphur in fuels and can reduce engine performance. ...

AI-powered intestinal ultrasound in inflammatory bowel disease: Advancing toward automated disease assessment.

The management of inflammatory bowel disease (IBD) relies on accurate disease assessment and close monitoring to guide therapy and evaluate treatment ...