COPD

Artificial intelligence to improve the detection and risk stratification of acute pulmonary embolism (AID-PE): protocol for a pragmatic quasi-experimental comparator study.

INTRODUCTION: Pulmonary embolism (PE) is a potentially fatal condition requiring timely diagnosis and treatment. CT pulmonary angiography (CTPA) is the gold standard for diagnosis and indicates PE severity through radiological markers of right heart strain. However, accurate interpretation and communication of these findings is often suboptimal in real-world practice. Artificial intelligence (AI) ...

A rapid diagnostic approach for COPD utilizing multimodal serum spectra integrated with machine learning algorithms.

Chronic Obstructive Pulmonary Disease (COPD) is a major global respiratory illness causing death and disability. Traditional methods lack consistent standards, often miss diagnoses, and cannot explore diseases' molecular relationships. Thus, there is a need for a diagnostic method that is both efficient and convenient. This study aimed to evaluate the potential of diagnosing COPD, Non-COPD (Pulmon...

Artificial Intelligence-Assisted Identification and Prevention of Chronic Obstructive Pulmonary Disease Using Biodegradable and Reusable Piezoelectric Elastomer/Poly(l-lactic acid) Composite Nanofiber Membrane.

Chronic obstructive pulmonary disease (COPD) is a respiratory disease imposing significant economic and health burdens to patients. The long latent pe...

Deep-Learning-Enhanced Living Biophotovoltaics: Predictive Photocurrent Modeling and Sensitive Herbicide Biosensing.

A cyanobacteria-based living biophotovoltaic (LBPV) system was developed by integrating Leptolyngbya sp. with conductive polymer-gold nanoparticle-mod...

Inhibition of the p38/JNK MAPK pathway mediated by circadian rhythm genes: Study of the mechanism of Linggan Wuwei Jiangxin decoction in the treatment of COPD.

ETHNOPHARMACOLOGICAL RELEVANCE: Chronic obstructive pulmonary disease (COPD) is a frequently encountered respiratory disease. Its clinical symptoms ar...

Identification of Key Physicochemical Characteristics Which Influence Epithelial-to-Mesenchymal Transition of Lung Cells after Exposure to Engineered and Natural Stone Dusts via a Hybrid Machine Learning Approach.

Exposure to respirable and inhalable dust from engineered stone is linked to lung diseases such as silicosis and COPD, yet the physicochemical propert...

Theoretical Insights on the Regulatory Mechanisms of Structure and Doping on the Photoluminescence of Ligand Protected Gold Nanoclusters.

ConspectusLigand-protected gold nanoclusters (Au NCs) occupy a unique region between molecules and bulk metals, garnering significant attention due to...

Light-Promoted Efficient Gold Recovery Enabled by a Polydopamine-Functionalized Covalent Organic Framework.

The rapid proliferation of artificial intelligence (AI) and information technologies is driving a sharp increase in global electronic waste, creating ...

Integrating multi-source data and machine learning to Decipher the psoriasis-COPD comorbidity.

Predicting the Apnea-Hypopnea index for the diagnosis of obstructive sleep apnea with cardiovascular and cancer comorbidity using wearable sleep-tracking devices.

INTRODUCTION: Obstructive Sleep Apnea (OSA) is a highly prevelance sleep breathing disorder that imposes, significant public health and economic burde...

Update on Non-Biological and RNA-Based Therapeutics in Chronic Inflammatory Diseases: Precision Medicine Through Small Molecules.

In the last decades, critical advancements in research technology and knowledge on disease mechanisms steered therapeutic approaches for chronic infla...

Commercial AI platforms improve reproducibility but fail to meet clinical precision thresholds for intracranial aneurysm measurement: implications for serial surveillance.

BACKGROUND: Intracranial aneurysm affect 3-7% of the global population, with rupture causing > 80% of non-traumatic subarachnoid hemorrhage and approx...

Nitrilotriacetic acid functionalized gold nanopillars enable stochastic detection and deep learning analysis of prolines and hydroxyprolines by surface enhanced Raman spectroscopy.

Proline hydroxylation is crucial for monitoring diseases related to collagen metabolism, analyzing metabolic pathways, and evaluating therapeutic or n...

Factors influencing long-term outcomes in lung transplantation: effective monitoring and comprehensive intervention.

PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge. Outcome determinants have expanded beyond pathop...

Governance Framework for Safe and Ethical Implementation of Artificial Intelligence in Surgery: A Modified-Delphi Consensus.

BACKGROUND: Artificial intelligence (AI)-enabled clinical decision support systems (CDSS) demonstrate performance comparable or superior to human expe...

Sculpting Superior Subnanometer Catalysts Directly from Inert Gold.

Bulk gold, renowned for its catalytic inertness, can be transformed into an exceptionally active catalyst by engineering undercoordinated sites on its...

Association and Agreement of Contact-Based Smartphone Photoplethysmography Compared With Electrocardiography: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Mobile health (mHealth), leveraging mobile devices for health measurement and promotion, is rapidly growing. Smartphone cameras can perfor...

Machine learning-assisted screening of small-molecule drugs for suppressing protein aggregation and ROS generation based on ECL and CV dual-mode signals amplified by DNA.

Screening of small-molecule drugs to suppress both protein aggregation and reactive oxygen species (ROS) generation is critical for developing therapi...

Development of machine learning-driven non-invasive diagnostic models for idiopathic membranous nephropathy in Chinese patients.

BACKGROUND: Idiopathic membranous nephropathy (IMN) is a major cause of nephrotic syndrome and end-stage renal disease, but the gold-standard diagnost...

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...