Pulmonology

Integrated Strategies for Nursing and Rehabilitation in Lung Cancer Patients.

This review delineates the pivotal role of nursing and rehabilitation in perioperative management and chemotherapy support for lung cancer patients, with a focus on complication prevention, nutritional support, pulmonary rehabilitation (PR), and the integration of emerging technologies to optimize patient outcomes and quality of life (QoL). This review systematically summarizes nursing and rehabil...

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 detection. We previously developed and validated LUS interpretation criteria in systemic sclerosis (SSc) and idiopathic inflammatory myopathy (IIM) showing excellent diagnostic performance and correlations with ILD severity. In this study, we applied deep learning to evaluate whether convolutional neura...

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 and may interrupt life-saving oncologic therapy o...

Cleft related facial skeletal surgery: an update.

PURPOSE OF REVIEW: This review provides a comprehensive update on advancements and evolving paradigms in cleft-related facial skeletal surgery. It eva...

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-effective diagnostic alternative to traditional imaging-ba...

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 disease (COPD), yet the contribution of artificial int...

Integration of multi-omics and machine learning to identify core genes in PANoptosisof lung adenocarcinoma and their mechanisms in the tumor microenvironment and therapeutic potential.

Lung adenocarcinoma (LUAD) is one of the leading causes of cancer-related deaths worldwide, and its complex tumor microenvironment (TME) is a key barr...

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

Pulmonary sarcoidosis is a heterogeneous granulomatous disease with an unpredictable clinical course, in which accurate assessment of disease activity...

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 spectral CT (DLCT) parameters for preoperative predictio...

Deep learning‑based ultra-high-resolution CT imaging of viral pneumonia at admission and after discharge.

Clinical decision support system for breathlessness.

PURPOSE OF REVIEW: This review summarizes high-level evidence on clinical decision support systems, both more classical rules-based and emerging artif...

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 need for early and accurate diagnosis. Precise segm...

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 platforms for health information. However, the qual...

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, the standard 6-Minute Walk Test (6MWT) is difficult...

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 particulates known to cause diverse pulmonary health eff...

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 synthetic data generation to predict unplanned 30-day hosp...

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 essential step in guiding treatment options and prognosi...

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 persons with TB nationwide were not diagnosed. Estimate...

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 define its prevalence in patients with esophageal...