Pulmonology

A Brønsted-Evans-Polanyi Relationship-Guided Machine Learning Model for Predicting H2 Activation Mechanism over Indium Oxide Surfaces across Various Oxygen Vacancies Coverages.

H2 activation mechanism governs the activity, selectivity, and stability of CO2 hydrogenation over In2O3 surfaces, which varies with the coverages of oxygen vacancies under the realistic reaction conditions. Herein, we systematically map H adsorption and H2 dissociation on cubic In2O3(111) across a broad range of oxygen vacancy coverages, explicitly distinguishing heterolytic cleavage at In-O pair...

Deep learning-based automated assessment of alveolar bone loss in CBCT for periodontitis.

OBJECTIVES: This study aimed to develop and validate a CBCT-based automated system for assessing radiographic alveolar bone loss (RBL) to improve the accuracy and efficiency of periodontitis diagnosis. METHODS: A total of 110 patients (2,796 teeth) with Stage I-IV periodontitis from four center were included. The nnU-Net framework was used to segment teeth, alveolar bone, and the cemento-enamel ju...

Identifying severe COVID-19 risk variants modulating enhancer reporter activity in lung cells.

Common genetic variants contribute to risk for complex human diseases. However, despite thousands of associations, variants modulating disease risk an...

Editorial for "RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization".

Anchor-free temporal localization of apnea events from EEG/EOG with state-space models.

Reduced-channel polysomnography (PSG) and electroencephalography/electrooculography (EEG/EOG) signals can support obstructive sleep apnea (OSA) screen...

Integrating CT Radiomics and Machine Learning for Preoperative Assessment of STAS Grading and Prognostic Stratification in Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: The distance of spread through air spaces (STAS) dissemination is associated with prognosis in lung adenocarcinoma (LUAD). T...

Evaluation of the performance and temporal variability of large language models in patient education regarding pneumothorax: a seven-day analysis.

This study investigates the readability, clinical reliability, and temporal consistency of artificial intelligence (AI) chatbots regarding pneumothora...

Prediction of bronchopulmonary dysplasia seven days after birth using respiratory and oxygenation timeseries with machine learning.

BACKGROUND: Accurate prediction of bronchopulmonary dysplasia (BPD) development would allow targeted early treatment. This study aims to develop a mac...

The future of pediatric gene therapy: CRISPR-Cas9, AI, and personalized medicine.

The future of pediatric gene therapy is being fundamentally reshaped by the convergence of CRISPR-Cas9 genome editing, artificial intelligence (AI), a...

Neoadjuvant Chemoradiotherapy on Postoperative Complications of Rectal Cancer: A Retrospective Study Integrating MRI Radiomics and Deep Learning.

Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer but increases postoperative complication (POC) risks due to tissue...

Explainable machine learning for early prediction and anatomical classification of pulmonary embolism in the emergency department.

BACKGROUND: Pulmonary thromboembolism (PTE) is a life‑threatening condition that requires prompt and accurate evaluation in the emergency department (...

A CT-based deep learning model for the automated risk stratification of refractory Mycoplasma pneumoniae pneumonia in children.

BACKGROUND: The accurate identification of children with refractory Mycoplasma pneumoniae pneumonia (RMPP) remains challenging. This study aimed to de...

Plasma proteomics and machine learning deliver non-invasive distinction between fibrotic hypersensitivity pneumonitis and idiopathic pulmonary fibrosis.

BACKGROUND: Hypersensitivity pneumonitis (HP) manifests as fibrotic (FHP) and non-fibrotic (NFHP) phenotypes. Clinically distinguishing FHP from idiop...

Development and validation of a routine blood test-based model to predict in-hospital postoperative pulmonary infection in older patients with hip fracture.

BACKGROUND: Postoperative pulmonary infection (PPI) is a common and serious complication in older adults undergoing hip fracture surgery, leading to p...

Glycosylation-related gene risk model and functional validation of OSTC and TUBA1C in lung adenocarcinoma.

INTRODUCTION: OSTC and TUBA1C drive the malignant progression of lung adenocarcinoma (LUAD) through the modulation of N-glycosylation and the PI3K/AKT...

AI-Assisted cardiomegaly screening via implicit morphological inference and human-in-the-loop validation.

Cardiomegaly screening via manual Cardiothoracic Ratio (CTR) measurement remains a clinical bottleneck, while contemporary deep learning solutions oft...

A USP15/KRT17-associated 13-gene prognostic cluster and functional validation in EGFR-mutant lung adenocarcinoma.

BACKGROUND: EGFR-mutant lung adenocarcinoma (LUAD) exhibits significant prognostic heterogeneity despite the efficacy of tyrosine kinase inhibitors. T...

From sites to structure to serology: a roadmap for structure-aware molecular evolution of antigenically evolving viruses.

The genomic deluge has pushed viral molecular evolution into a site-resolved era. For antigenically evolving viruses such as influenza and severe acut...

Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

This study aimed to develop and validate an interpretable machine learning (ML) model using routine laboratory data to support clinical decision-makin...

Evaluating Large Reasoning Models Versus Human Multidisciplinary Teams in Lung Cancer Decision-Making: Real-World Study.

BACKGROUND: Large language models (LLMs) and large reasoning models (LRMs) have shown excellent performance on medical benchmarks, although evaluation...