Pulmonology

Leveraging large language models for patient-ventilator asynchrony detection.

OBJECTIVES: The objective of this study is to evaluate whether large language models (LLMs) can achieve performance comparable to expert-developed deep neural networks in detecting flow starvation (FS) asynchronies during mechanical ventilation.

Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.

BACKGROUND: Indeterminate pulmonary nodules (IPNs) are commonly biopsied to ascertain a diagnosis of lung cancer, but many are ultimately benign. The Lung Cancer Prediction (LCP) score is a commercially available deep learning radiomic model with strong diagnostic performance in incidentally identified IPNs, but its potential use to reduce the need for invasive procedures has not been evaluated in...

Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry.

INTRODUCTION: Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath is a rapidly evolving field aimed at harnessing e...

A multi-view CNN model to predict resolving of new lung nodules on follow-up low-dose chest CT.

OBJECTIVE: New, intermediate-sized nodules in lung cancer screening undergo follow-up CT, but some of these will resolve. We evaluated the performance...

A dataset of microscopic spirometra mansoni for medical image segmentation.

Accurate diagnosis of adult Spirometra mansoni infections remains challenging, due to the limited sensitivity and high cost associated with immunodiag...

Clinical efficacy of AI in lung SABR planning: A comparative retrospective analysis.

This study evaluated the effectiveness of an integrated Artificial Intelligence (AI) planning tool in a lung stereotactic ablative body radiotherapy (...

Deep learning-based contour propagation in magnetic resonance imaging-guided radiotherapy of lung cancer patients.

Fast and accurate organ-at-risk (OAR) and gross tumor volume (GTV) contour propagation methods are needed to improve the efficiency of magnetic resona...

European Respiratory Society Clinical Practice Guideline on Telemedicine in Home Mechanical Ventilation.

BACKGROUND: With the increasing prevalence of patients on home mechanical ventilation (HMV), changing indications, shortage of hospital resources, and...

Development, deployment, and feature interpretability of a three-class prediction model for pulmonary diseases.

PURPOSE: To develop a high-performance machine learning model for predicting and interpreting features of pulmonary diseases.

Correction: Data-driven machine learning algorithm model for pneumonia prediction and determinant factor stratification among children aged 6-23 months in Ethiopia.

Machine learning prediction models for stroke-associated pneumonia:Meta-analysis.

OBJECTIVE: The heterogeneity of machine learning (ML) models predicting the risk of stroke-associated pneumonia (SAP) is considerable. This study aims...

Exploring the complex interplay between oral infection, periodontitis, and robust microRNA induction, including multiple known oncogenic miRNAs.

() is an oral commensal bacterium that can become pathogenic and is associated with periodontitis, adverse pregnancy outcomes, and colorectal cancer ...

A Novel nor@DHB Matrix for Direct Microbial Analysis in Lung Cancer Tissues.

Dynamic changes occurring in the lung microbiota can impact the initiation, progression, and prognosis of lung cancer (LC). Consequently, the developm...

[AI-enabled clinical decision support systems: challenges and opportunities].

Clinical decision-making is inherently complex, time-sensitive, and prone to error. AI-enabled clinical decision support systems (CDSS) offer promisin...

Safety of nonselective nonsteroidal anti-inflammatory drugs in cardiac surgery: a historical cohort study.

PURPOSE: Pain management after cardiac surgery is imperative, as inadequate analgesia can increase the risk of myocardial ischemia, thromboembolism, a...

BronchoGAN: anatomically consistent and domain-agnostic image-to-image translation for video bronchoscopy.

Purpose The limited availability of bronchoscopy images makes image synthesis particularly interesting for training deep learning models. Robust image...

Efficacy of an Automated Pulmonary Embolism (PE) Detection Algorithm on Routine Contrast-Enhanced Chest CT Imaging for Non-PE Studies.

The urgency to accelerate PE management and minimize patient risk has driven the development of artificial intelligence (AI) algorithms designed to pr...

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, cur...

Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray.

Thoracic diseases, including pneumonia, tuberculosis, lung cancer, and others, pose significant health risks and require timely and accurate diagnosis...

Streamlining tuberculosis detection with foundation model-based weakly supervised transformer.

Tuberculosis (TB) remains a major global health challenge, particularly in low- and middle-income countries. Traditional microscopy-based diagnostics ...