Pulmonology

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 evaluates recent literature concerning the integration of artificial intelligence in surgical prediction, optimal orthognathic surgical sequencing, the utility of virtual surgical planning (VSP) and patient-specific implants (PSIs), strategies for manag...

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-based methods. This study proposes a deep learning-based optimization framework for automated respiratory disease classification using the publicly available ICBHI 2017 Respiratory Sound Database (Kaggle version), comprising 920 recordings from 126 sub...

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...

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 (TB) and the growing threat of multidrug-resistant...

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 saving lives and ensuring effective treatment for pa...

Gut microbial extracellular vesicles modulate the development of metabolic dysfunction-associated steatohepatitis through the gut-liver axis.

Metabolic dysfunction-associated steatohepatitis (MASH) represents a growing global health challenge due to its propensity to progress to irreversible...