Pulmonology

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). This study aimed to develop a computed tomography (CT) radiomics-based machine learning model to predict STAS grade. MATERIALS AND METHODS: Retrospective data included 293 LUAD patients for training/internal validation and 92 from the National Lung Sc...

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 pneumothorax information. A question bank comprising 40 patient-centered queries was deployed across three large language models (ChatGPT, Gemini, Copilot), stratified by two access tiers and two prompting strategies (zero-shot versus the optimized PROMPORT str...

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...

Identification of lactate metabolism-related genes as kidney fibrosis biomarkers through integrated transcriptomic and experimental analyses.

Kidney fibrosis, the final pathological outcome of chronic kidney disease, lacks reliable biomarkers, and the role of lactylation in its pathogenesis ...

Understanding HFpEF Through Imaging: Strengths, Limitations, and Current State of the Art.

Heart failure with preserved ejection fraction (HFpEF) is a clinical syndrome characterized by dyspnea caused by hemodynamic congestion, which develop...

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...

Identifying sex-specific sub-phenotypes of Alzheimer's disease progression using longitudinal electronic health records.

BACKGROUND: Alzheimer's Disease (AD) is a complex neurodegenerative disorder, with women comprising nearly two-thirds of individuals with AD. However,...

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer scr...

Multiparametric PET/CT Tensor Radiomics for Stability-Aware Machine Learning in Lung Cancer Survival Prediction.

To address the challenges of model instability and limited generalizability in radiomics-based lung cancer prognosis, we developed a robust multiparam...