COPD

Large Language Models Exhibit High Performance as Computable Phenotypes for Pediatric Asthma Exacerbation Detection in a Retrospective, Observational Study of Emergency Medical Services Encounters.

OBJECTIVES: Pediatric asthma exacerbations are a common emergent condition treated by prehospital emergency medical services (EMS). However, retrospective identification of those patients for research, educational, and quality improvement purposes can be difficult given the unique structure of EMS' electronic health records. Computable phenotypes are algorithms used to identify patients of interes...

Development of an artificial intelligence prediction model for moderate-to-severe COPD exacerbations using continuous multiple unobtrusive sensors: protocol of a multicentre prospective observational study.

INTRODUCTION: Exacerbations, impaired health-related quality of life (HRQoL) and reduced exercise capacity increase the risk of hospitalisations and death in chronic obstructive pulmonary disease (COPD). However, their monitoring relies on in-person assessments, potentially delaying early care. While smart sensing technologies can enable remote monitoring, their use in predicting disease worsening...

Hybrid deep learning approach for early emphysema diagnosis combining fuzzy C-means, TransUNet, and faster mask R-CNN.

Emphysema is a chronic condition of the lungs and it has to be diagnosed at an early age as it can harm the lungs effectively as they can be treated a...

Chest Radiograph-Derived Age Acceleration as an Early Marker of Pulmonary Dysfunction in Middle-Aged Asians.

BACKGROUND: Deep learning-derived, chest radiographic (CXR) age may capture subclinical structural changes associated with spirometric impairment. RES...

AI-Driven Heart Failure Decision Support in Skilled Nursing Facilities.

Heart failure management in skilled nursing facilities (SNFs) is complicated by limited access to specialists, incomplete clinical documentation, and ...

How to quickly determine whether patients with chronic cough need corticosteroid treatment--construction of a predictive model for corticosteroid-responsive cough in chronic cough.

Patients with chronic cough need to undergo a wide range of tests and rely on empirical medication to determine the underlying cause. Corticosteroid-r...

A machine-learning approach to predict additional treatment after Bacillus Calmette-Guérin induction in non-muscle-invasive bladder cancer.

Non-muscle invasive bladder cancer (NMIBC) comprises ~ 75% of newly diagnosed bladder cancer, with high-risk NMIBC associated with high rates of recur...

An Interpretable Multidimensional Acoustic Physiology Map for COPD Using Digital Lung Sounds.

BACKGROUND: Lung sound analysis may capture chronic obstructive pulmonary disease (COPD) related physiology, but many methods are hard to interpret cl...

Using Elicit AI research assistant for data extraction in systematic reviews: A feasibility study across environmental and life sciences.

Data extraction in systematic reviews, maps, and meta-analyses is time-consuming and prone to human error or subjective judgment. Large Language Model...

Explainable machine learning for estimation of elevated left ventricular filling pressure: a multicenter validation.

BACKGROUND: Guideline-recommended algorithms (GL-algorithm) often results in indeterminate left ventricular filling pressure (LVFP). Despite high accu...

Artificial intelligence-based models in predicting acute exacerbations and diagnosing pediatric asthma: a systematic review and meta-analysis.

PURPOSE: This systematic review and meta-analysis evaluated the performance of artificial intelligence (AI)-based models in diagnosing pediatric asthm...

Deriving Clavien-Dindo Classification from Administrative Data: Development and External Validation in Hepatobiliary Surgery.

INTRODUCTION: Routine electronic health records (HER)/administrative data could enable time- and cost-efficient, real-time surveillance and health-eco...

Using artificial intelligence-assisted retinal imaging devices operated by non-specialist workers in detecting diabetic retinopathy in Sri Lanka.

BACKGROUND: Diabetic retinopathy (DR), a microvascular complication of diabetes, is an important cause of preventable blindness and can cause a signif...

The evolution of scientific knowledge in childhood asthma over time.

Paediatric asthma management has undergone a significant transformation from rudimentary assessments in the early 20th century to sophisticated diagno...

Multicentre prospective cohort study to develop and validate a machine learning-based model for predicting 6-month all-cause mortality in elderly patients with advanced chronic obstructive pulmonary disease in China: study protocol.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) has an unpredictable clinical course, causing difficulties in short-term mortality predicti...

Correlation of Patient-Reported Symptoms With Rhinogram Features Beyond Simple Airway Resistance.

INTRODUCTION: Rhinomanometry, a reference measure for the nasal airway, is often considered a research tool with only weak-to-moderate correlations wi...

Optimizing camera placement in multi-view markerless motion capture: a validation study against gold-standard kinematics for static and dynamic tasks.

OBJECTIVE: This study aimed to determine the optimal camera configuration for a markerless motion capture system, which may offer a lower-cost alterna...

From trial-and-error to intelligent prediction: Machine learning drives eco-efficient gold leaching in e-waste.

Recovering gold (Au) from e-waste is critical for sustainable resource management, yet traditional optimization methods face challenges such as excess...

Pulmonary vascular volume heterogeneity in association with emphysema: a multicenter study based on non-contrast chest CT.

PURPOSE: To investigate the associations between emphysema and pulmonary vessels in patients with chronic obstructive pulmonary disease (COPD) and con...

Predicting Lung Function from Voice Recordings Using Machine Learning: An Optimised Approach.

Spirometry is a crucial diagnostic test for pulmonary diseases, where measures including Forced Expiratory Volume in one second (FEV1) have diagnostic...