Pulmonology

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study aims to develop a deep learning radiological-pathological-clinical (DLRPC) model that integrates computed tomography (CT) images, hematoxylin and eos...

Predictive models of severe disease in patients with COVID-19 pneumonia at an early stage on CT images using topological properties.

Prediction of severe disease (SVD) in patients with coronavirus disease (COVID-19) pneumonia at an early stage could allow for more appropriate triage and improve patient prognosis. Moreover, the visualization of the topological properties of COVID-19 pneumonia could help clinical physicians describe the reasons for their decisions. We aimed to construct predictive models of SVD in patients with C...

Managing chronic disease in the digital era: The role of telemedicine apps and platforms.

Chronic diseases such as diabetes, heart disease, or asthma are one of the biggest health challenges of the modern world. Their management requires co...

F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.

BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasivel...

Intermittent hypoxemia during hemodialysis: AI-based identification of arterial oxygen saturation saw-tooth pattern.

BACKGROUND: Maintenance hemodialysis patients experience high morbidity and mortality, primarily from cardiovascular and infectious diseases. It was d...

Altered static and dynamic functional network connectivity and combined Machine learning in asthma.

Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. Previous neuroimaging studies have shown structura...

OPTUNA optimization for predicting chemical respiratory toxicity using ML models.

Predicting molecular toxicity is an important stage in the process of drug discovery. It is directly related to medical destiny and human health. This...

An explainable artificial intelligence framework for weaning outcomes prediction using features from electrical impedance tomography.

BACKGROUND: Prolonged mechanical ventilation (PMV) might cause ventilator-associated pneumonia and diaphragmatic injury, and may lead to worsening cli...

Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction.

INTRODUCTION: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of publi...

Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.

There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in pr...

Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms.

Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics...

Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning.

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by elevated pulmonary arterial pressure, leading to right ...

Beyond immunosuppression: decoding systemic immune dysregulation in ICU-acquired pneumonia.

Integrating machine learning and neural networks for new diagnostic approaches to idiopathic pulmonary fibrosis and immune infiltration research.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease with a fatal outcome, known for its rapid progression and unpredictabl...

Precision Strike Strategy for Liver Diseases Trilogy with Xiao-Chai-Hu Decoction: A Meta-Analysis with Machine Learning.

BACKGROUND AND PURPOSE: The progression from hepatitis to liver fibrosis (LF) and ultimately to hepatic carcinoma (HCC) represents the advanced stages...

Unsupervised non-small cell lung cancer tumor segmentation using cycled generative adversarial network with similarity-based discriminator.

BACKGROUND: Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods r...

Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.

Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool w...

An integrated machine learning model of transcriptomic genes in multi-center chronic obstructive pulmonary disease reveals the causal role of TIMP4 in airway epithelial cell.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome, resulting in inconsistent findings across studies. Identifying a...

The predictive role of identifying frailty in assessing the need for palliative care in the elderly: the application of machine learning algorithm.

BACKGROUND: Palliative care is a key component of integrated care to improve care quality and reduce hospitalization costs for patients with chronic o...

AI-based phenotyping of hepatic fiber morphology to inform molecular alterations in metabolic dysfunction-associated steatotic liver disease.

BACKGROUND AND AIMS: Hepatic fiber morphology may significantly enhance our understanding of molecular alterations in metabolic dysfunction-associated...