Pulmonology

Root of Prunus persica (taoshugen) ameliorated renal fibrosis by inhibiting TGF-β signaling via upregulating Pmepa1 in mice with unilateral ureter obstruction.

ETHNOPHARMACOLOGICAL RELEVANCE: Various parts of Prunus persica (L.) Batsch (peach) exhibit medicinal properties and are utilized in traditional Chinese medicine (TCM) for therapeutic purposes. Notably, the root of P. persica, referred to as "taoshugen" in Chinese, is utilized by experienced TCM practitioners for the treatment of liver cirrhosis, suggesting its potential efficacy in mitigating org...

Artificial Intelligence for the Detection of Patient-Ventilator Asynchrony.

Patient-ventilator asynchrony (PVA) is a challenge to invasive mechanical ventilation characterized by misalignment of ventilatory support and patient respiratory effort. PVA is highly prevalent and associated with adverse clinical outcomes, including increased work of breathing, oxygen consumption, and risk of barotrauma. Artificial intelligence (AI) is a potentially transformative solution offer...

5-Repurposed Drug Candidates Identified in Motor Neurons and Muscle Tissues with Amyotrophic Lateral Sclerosis by Network Biology and Machine Learning Based on Gene Expression.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that leads to motor neuron degeneration, muscle weakness, and respirat...

Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infection.

BACKGROUND: Lower respiratory tract infections (LRTIs) are a leading cause of mortality worldwide and can be difficult to diagnose in critically ill p...

Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China.

BACKGROUND: Computer-aided detection (CAD) software has been introduced to automatically interpret digital chest X-rays. This study aimed to evaluate ...

Therapeutic potential of allosteric HECT E3 ligase inhibition.

Targeting ubiquitin E3 ligases is therapeutically attractive; however, the absence of an active-site pocket impedes computational approaches for ident...

Addressing model discrepancy in a clinical model of the oxygen dissociation curve.

Many mathematical models suffer from model discrepancy, posing a significant challenge to their use in clinical decision-making. In this article, we c...

Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs among patients with traumatic brain injury. Accurat...

Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review.

BACKGROUND: Pleural diseases represent a significant healthcare burden, affecting over 350 000 patients annually in the US alone and requiring accurat...

Development and validation of machine learning models for early diagnosis and prognosis of lung adenocarcinoma using miRNA expression profiles.

ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using Machine learning（ML）algorithms, aiming to enhance...

Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma.

BACKGROUND: Unlike lung adenocarcinoma, patients with advanced squamous carcinoma exhibit a low proportion of driver gene positivity, with fewer effec...

Predictive models of epidermal growth factor receptor mutation in lung adenocarcinoma using PET/CT-based radiomics features.

BACKGROUND: Lung adenocarcinoma (LAC) comprises a substantial subset of non-small cell lung cancer (NSCLC) diagnoses, where epidermal growth factor re...

A CNN-transformer fusion network for predicting high-grade patterns in stage IA invasive lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma (LUAD) with the high-grade patterns (HGPs) has the potential for rapid metastasis and frequent recurrence. Th...

Right ventricular dysfunction following tetralogy of Fallot correction: anatomical determinants and therapeutic strategies.

Right ventricular dysfunction following surgical correction of tetralogy of Fallot (TOF) remains a major determinant of long-term morbidity and mortal...

Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.

PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remain...

Deep Learning-driven Microfluidic-SERS to Characterize the Heterogeneity in Exosomes for Classifying Non-Small Cell Lung Cancer Subtypes.

Lung cancer exhibits strong heterogeneity, and its early diagnosis and precise subtyping are of great importance, as they can increase the ability to ...

Water quality parameters-based prediction of dissolved oxygen in estuaries using advanced explainable ensemble machine learning.

The dissolved oxygen (DO) is crucial for the ecological health of estuaries and bays. However, human activities, land-sea interactions, and the unclea...

Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach.

BACKGROUND: Non-small-cell lung cancer (NSCLC) and its surgery significantly increase the venous thromboembolism (VTE) risk. This study explored the V...

Immune profile and routine laboratory indicator-based machine learning for prediction of lung cancer.

INTRODUCTION: Early diagnosis of lung cancer is still a challenge by using current diagnostic methods.

Machine Learning Identification of Neutrophil Extracellular Trap-Related Genes as Potential Biomarkers and Therapeutic Targets for Bronchopulmonary Dysplasia.

Neutrophil extracellular traps (NETs) play a key role in the development of bronchopulmonary dysplasia (BPD), yet their molecular mechanisms in contri...