Pulmonology

Artificial Intelligence-Aided Lung Ultrasound Detection of Interstitial Lung Disease in Systemic Sclerosis and Inflammatory Myopathy.

BACKGROUND: Lung ultrasound (LUS) is a sensitive, low-cost, and radiation-free modality for ILD dete...

Artificial Intelligence-Enabled Prediction of Reversible Versus Irreversible Chemotherapy-Induced Myocardial Injury: Toward Precision Cardio-Oncology.

Cancer therapy-related cardiac dysfunction remains a major cause of morbidity among cancer survivors...

Cleft related facial skeletal surgery: an update.

PURPOSE OF REVIEW: This review provides a comprehensive update on advancements and evolving paradigm...

Novel deep learning-based optimization framework for the classification of respiratory diseases using lung sound analysis.

Respiratory disease classification using lung sound analysis offers a non-invasive and cost-effectiv...

Exploring AI and ML in managing overlap between cardiovascular disease and asthma or COPD: a scoping review.

Cardiovascular disease (CVD) is a major comorbidity in asthma and chronic obstructive pulmonary dise...

FDG PET in pulmonary sarcoidosis: An update and future aspects.

Pulmonary sarcoidosis is a heterogeneous granulomatous disease with an unpredictable clinical course...

Dual-layer spectral CT for predicting spread through air spaces in lung adenocarcinoma: a dual-center study.

OBJECTIVES: To investigate the value of machine learning classifiers incorporating dual-layer spectr...

Regulating dopant depth in nitrogen-doped biphenylene nanoribbons for efficient oxygen reduction reaction.

One-dimensional carbon nanostructures offer unique pathways to modulate the local electronic environ...

Clinical decision support system for breathlessness.

PURPOSE OF REVIEW: This review summarizes high-level evidence on clinical decision support systems, ...

Lung cancer segmentation Using the Att-U-Net Model on PET-CT Images.

INTRODUCTION: Lung cancer is the leading cause of cancer-related deaths worldwide, emphasizing the n...

From phenotypes to trajectories: Machine learning in asthma beyond labels.

Evaluating the quality of online health information: A comparative study of COPD patient information in Facebook forums versus ChatGPT.

BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) increasingly turn to online p...

A novel machine learning model of smartphone-based 1-minute sit-to-stand test for prediction of six-minute walk test distance in patients with COPD.

BACKGROUND: Regular assessment of exercise tolerance is essential for managing COPD, nevertheless, t...

Interpretable Machine Learning to Understand Wildfire Toxicity: Bridging Chemicals, Omics, and Toxicological Outcomes via Symbolic Regression with Novel Feature Scoring.

Wildfire smoke exposures are increasingly common, consisting of complex mixtures of gases and partic...

Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study.

OBJECTIVES: To develop and evaluate an explainable machine learning framework enhanced with syntheti...

Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining.

The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essent...

Accelerating tuberculosis diagnosis in Mozambican prisons using digital chest X-rays with computer-aided detection: a longitudinal, comprehensive health intervention.

BACKGROUND: Mozambique has a high burden of tuberculosis (TB) and in 2021, an estimated 18,000 perso...

Prospectively screening for venous thromboembolism in patients with esophagectomy for cancer improves survival: The complexity of simplicity.

BACKGROUND: We implemented a prospective screening program to detect deep venous thromboembolism and...

Temporal Knowledge Discovery in Drug-Resistant Tuberculosis: A Decade-Long Machine Learning Analysis From Egyptian Clinical Data.

BACKGROUND: Advanced predictive tools are required due to the worldwide persistence of tuberculosis ...

Modified ShuffleNet trained on gradient pattern and shape-based features for lung cancer classification with improved M-SegNet segmentation.

Lung cancer (LC) is one of the leading causes of death globally. Early detection is essential for sa...

Multicenter Histology Image Integration and Multiscale Deep Learning Support Machine Learning-Enabled Pediatric Sarcoma Classification.

UNLABELLED: Pediatric sarcomas present diagnostic challenges due to their rarity and diverse subtype...