Pulmonology

Exploring the gut-lung axis in post-liver transplant acute lung injury: A multi-omics approach.

Acute lung injury (ALI) is a significant post-operative complication of liver transplant (LT), with mounting evidence suggesting a role for the gut-lung axis. However, the mechanistic link between gut microbiota dysbiosis and ALI pathogenesis in LT recipients remains poorly understood. This hybrid translational investigation integrates transcriptomic profiling (bulk and single-cell RNA-seq), immun...

Predicting 5-Year Mortality in Non-Small-Cell Lung Cancer Using the Korean Central Cancer Registry: Model Development and Validation Study.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is one of the most common cancers and a leading cause of cancer-related mortality, making prognostic prediction clinically essential. Machine learning models are increasingly used to assess prognosis; however, developing systems that combine high discrimination with clear, clinically interpretable reasoning remains challenging. OBJECTIVE: This study a...

Digital Hydrogel Fluorescent-Enhancing Microspheres via CRISPR/Cas12a for Amplification-Free Relative Quantification of Nucleic Acids.

CRISPR/Cas systems hold great promise for molecular diagnostics, but their amplification-free applications are hampered by weak signals and poor quant...

Deep learning-based spatiotemporal estimation of lesion changes for patient-level assessment of breast cancer lung metastases on longitudinal CT.

Clinical management of breast cancer lung metastasis is challenging because of the complexity of dynamic lesion assessment. Traditional methods based ...

Integrated transcriptomics, network pharmacology and clinical expression validation reveal the prognostic significance of PANoptosis-related genes in cordycepin-treated lung adenocarcinoma.

BACKGROUND: Studies have shown that PANoptosis is increasingly involved in cancer and cancer treatment. The Cordycepin has also been found to be invol...

Deep learning layer-specific collagen quantification correlates with activity and is associated with outcomes in Crohn's disease.

BACKGROUND & AIMS: Intestinal fibrosis remains a major unmet need in inflammatory bowel disease (IBD). Although collagen deposition is the defining fe...

Integrative single-cell and spatial transcriptomics analysis reveals a baicalein-responsive 10-gene signature for non-small cell lung cancer.

BACKGROUND: Non‑small cell lung cancer (NSCLC) remains a leading cause of cancer‑related mortality worldwide. Baicalein, a natural flavonoid, has show...

CT ASSESSMENT OF BODY COMPOSITION AND LUNG EVOLUTION IN CYSTIC FIBROSIS AFTER ELEXACAFTOR-TEZACAFTOR-IVACAFTOR: A COHORT STUDY.

BACKGROUND: Elexacaftor-Tezacaftor-Ivacaftor (ETI) therapy markedly improves pulmonary function in people with cystic fibrosis (pwCF) but induces weig...

Machine learning methods identified cellular senescence-related hub molecules in sepsis-induced acute respiratory distress syndrome (ARDS) and their upstream regulatory network.

BACKGROUND: Sepsis-induced ARDS demonstrated greater severity and higher mortality compared to ARDS triggered by other factors. In this article, we co...

Emerging Applications of Artificial Intelligence in Pediatric Care.

Artificial intelligence (AI) technologies such as machine learning (ML), deep learning (DL), predictive analytics and other tools are rapidly changing...

Diagnostic accuracy of AI-Based models for pulmonary edema detection: A systematic review and Meta-Analysis.

BACKGROUND: Pulmonary edema is a life-threatening condition caused by fluid accumulation in the lungs that impairs gas exchange. Machine learning mode...

An interpretable machine-learning model for post-admission reassessment of bloodstream infection risk in ICU patients with pneumonia.

The aim of this study is to develop and validate a machine learning-based predictive model to assess the risk of acquired bloodstream infection (BSI) ...

Cross-population validation of the TyG-ABSI index as a novel predictor for chronic obstructive pulmonary disease: an integrated analysis using logistic regression and explainable machine learning.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is increasingly recognized as a systemic inflammatory condition closely linked to metabolic d...

Can AI chatbots effectively respond inquiries for patients with Pulmonary Arterial Hypertension about exercise and physical activity: A comparative study of three chatbots.

OBJECTIVE: The utilization of artificial intelligence-based chatbots in the healthcare field is increasingly prevalent. Nonetheless, the quality of re...

Stacking machine learning model for risk stratification of acute respiratory distress syndrome after traumatic brain injury: a multicenter retrospective study.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication after traumatic brain injury (TBI), and early risk stratification may ...

YOLO-geochemical integration for real-time aeolian dust monitoring: a critical review of signatures, health risks, and policy implications.

Aeolian dust is one of the most pervasive natural air pollutants, strongly influencing atmospheric chemistry, visibility, climate feedback, and human ...

Using the Machine Learning Algorithm XGBoost to Understand the Correlates of Wearing Hearing Protection in Central States' Agricultural Producers.

PURPOSE: Hearing loss is a common work-related condition. Estimates suggest that 46%-86% of agricultural workers have hearing loss. Agricultural safet...

Multimodal deep learning integration of clinical, dosiomics, and radiomics features to predict toxicity in breast cancer patients undergoing hypofractionated radiotherapy.

BACKGROUND AND PURPOSE: Radiation dermatitis (RD) and superficial soft tissue fibrosis are common toxicities among the patients with breast cancer rec...

Multidimensional proteomics and explainable AI feature selection identify cross-platform lung cancer molecular signature in blood plasma.

BACKGROUND: Lung cancer is the leading cause of cancer mortality worldwide despite the availability of low-dose computed tomography (LDCT) for screeni...

Physics-informed neural network-based simulation of pulmonary arterial hemodynamics abnormalities.

OBJECTIVES: To predict abnormal pulmonary artery hemodynamics caused by ventricular septal defect (VSD) using Physics-Informed Neural Networks (PINN) ...