Pulmonology

[Advances in multi-source medical data-driven identification and spatiotemporal cluster analysis of acute respiratory infections].

Acute respiratory infections (ARIs) are characterized by high morbidity, strong transmissibility, and non-specific clinical manifestations, posing substantial challenges to conventional single-source surveillance systems for early warning. This review systematically summarizes recent advances in ARIs identification and spatiotemporal cluster analysis based on multi-source medical data, focusing on...

A renewed focus on carbon uptake and use to enhance crop performance in the face of rising temperatures.

Increasing crop production to meet global food demand amid a more unstable climate is a challenge that requires new approaches from science and technology. To meet this challenge, plant physiologists must coordinate efforts with crop breeders to select appropriate traits and associated genes that drive improvements in crop performance. However, improvements in yield gain and yield quality are ofte...

Socioeconomic drivers of riverine biochemical oxygen demand: Insights from interpretable machine learning.

Biochemical oxygen demand (BOD5) is a comprehensive indicator for assessing organic pollution and water quality in rivers. Socioeconomic factors, such...

Mechanics, Fracture, and Fragmentation of Thrombi: A Computational Study Review.

Thrombosis drives myocardial infarction, acute ischemic stroke and pulmonary embolism, yet more than half of patients undergoing mechanical thrombecto...

Preoperative Optimization for Ventral Hernia Repair: Augmented Evidence Review.

BACKGROUND: Preoperative optimization is widely recommended for patients undergoing ventral hernia repair. However, the clinical impact of individual ...

High FDG Uptake in the Non-cancerous Lung Predicts Immune-Related Adverse Events and Poor Prognosis in Patients with Lung Cancer Treated with Immune Checkpoint Inhibitors.

RATIONALE AND OBJECTIVES: Immune checkpoint inhibitors (ICIs) have improved survival in non-small cell lung cancer (NSCLC); however, predicting immune...

Sex differences in microvascular patterns associated with low- and high-risk for cardiovascular disease.

BACKGROUND: The role of the microcirculation in cardiovascular health in males and females is not fully understood. Skin microvascular function can be...

Phenotypic Clustering of Idiopathic Pulmonary Arterial Hypertension: Insights Into Pulmonary Vascular and Cardiometabolic Co-Morbidity Trajectories.

Idiopathic pulmonary arterial hypertension (IPAH) exhibits significant clinical heterogeneity, necessitating a precision medicine approach. This study...

Biochemistry-based machine learning algorithms in differentiating pleural effusion: current status and perspective.

The differential diagnosis of pleural effusion remains challenging. Microbiological and cytopathological examinations are considered the gold standard...

AI-Driven Discovery of a Hydrophobic-Tag Degrader Targeting NSD3 for Lung Squamous Carcinoma Therapy.

Nuclear receptor-binding SET domain protein 3 (NSD3) is a histone H3K36 methyltransferase implicated in lung squamous cell carcinoma, yet chemical tar...

MULTIPREVENT: Integrated screening for smoking-related multimorbidity using low-dose chest computed tomography.

OBJECTIVES: Tobacco consumption, combined with individual genetic predispositions, contributes to an age-dependent risk not only for lung cancer but a...

Improving Follow-Up of Incidental Pulmonary Nodules in the Emergency Department Using an Artificial Intelligence-Supported Workflow.

BACKGROUND: Incidental pulmonary nodules (IPNs) are frequently identified on computed tomography (CT) scans but are often associated with poor rates o...

Sex-specific machine learning improves prediction of incident and prevalent COPD.

BACKGROUND: Computed tomography imaging with machine learning can predict incident and prevalent chronic obstructive pulmonary disease (COPD), however...

Machine learning-based identification of cardiovascular risk modifiers in patients with very high LDL cholesterol: A cross-sectional study.

Individuals with LDL cholesterol (LDL-C) ≥ 190 mg/dL face a markedly increased risk of major adverse cardiovascular events (MACE). Traditional risk ca...

Longitudinal Changes in Acid-Base Parameters From Dialysis Initiation to Death in Maintenance Hemodialysis Patients.

INTRODUCTION: Blood gas analysis is routinely performed in hemodialysis patients to monitor acid-base status and serum potassium. Despite frequent tes...

Deep Learning-Based Lung Cancer Segmentation and Volumetric Analysis Using CT Imaging: A Comprehensive Survey.

Lung cancer is one of the most prevalent causes of cancer-related deaths in the world, and in this context, accurate estimation of tumor burden and tr...

Fibrosis regression in chronic liver disease: the pathologist's view.

Numerous observations have indicated that significant amounts of liver fibrosis can either completely disappear or be substantially remodelled followi...

Multi-component radiological model based on intratumoral CT threshold segmentation for predicting visceral pleural invasion in lung adenocarcinoma ≤ 30 mm.

OBJECTIVES: This retrospective study aims to investigate the value of intratumoral computed tomography (CT) threshold segmentation in radiomics, deep ...

Prediction of effluent biochemical and chemical oxygen demand in Lake Manzala Hybrid Constructed Wetlands, Egypt using a linear regression-gradient boosting framework.

This study proposes an interpretable machine learning framework for predicting effluent quality in the Lake Manzala Hybrid Constructed Wetlands (HCWs)...

A Machine Learning-Based Multimodal Model Integrating Radiomics and Clinical Features for Predicting Interstitial Lung Disease: Development and External Validation.

RATIONALE AND OBJECTIVES: To develop and validate a multimodal model for predicting the risk of interstitial lung disease (ILD) by integrating radiomi...