Pulmonology

Leveraging computer vision systems for monitoring hutch-housed dairy calves.

Computer vision systems (CVS) have emerged as a powerful technology for animal monitoring. However, there is limited research on CVS for behavior monitoring of hutch-housed dairy calves, which account for >50% of all calf housing in the United States. The objectives of this study were to (1) develop a CVS to monitor animal location and posture of hutch-housed dairy calves; (2) compare the predicti...

A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses.

Ventilation quality in summer layer houses is critical for heat stress prevention, production performance, and poultry welfare. Addressing the issue of "qualified environmental parameters but chicken discomfort" caused by traditional methods overlooking spatial heterogeneity and individual differences, a dynamic ventilation quality assessment method based on panting behavior detection in laying he...

High burden of premature ventricular contractions upregulates transcriptional markers of inflammation and promotes adverse cardiac remodeling linked to cardiomyopathy.

Premature ventricular contractions (PVCs) are the most prevalent ventricular arrhythmia in adults. High PVC burden can lead to left ventricular (LV) s...

Predictive model of malignancy probability in pulmonary nodules based on multicenter data.

OBJECTIVES: To study the characteristic factors associated with the occurrence of malignant nodules in patients presenting with pulmonary nodules, dev...

Impact of a deep-learning image reconstruction algorithm on image quality and detection of solid lung lesions.

PURPOSE: To compare the impact of a deep-learning image reconstruction algorithm (Precise Image) with an iterative reconstruction algorithm on image q...

A systematic review and meta-analysis of artificial intelligence software for tuberculosis diagnosis using chest X-ray imaging.

BACKGROUND: Pulmonary tuberculosis (PTB) remains a global public health challenge, with 10.8 million new cases reported in 2023. Early diagnosis is cr...

Identification and validation of hypoxia-associated genes positively correlated with in pulmonary adenocarcinoma.

BACKGROUND: Hypoxia contributes to the proliferation, migration, and chemotherapy resistance of lung adenocarcinoma (LUAD). This study aimed to identi...

A Bayesian deep learning model with consolidation-to-tumor ratio (CTR) prior revolutionizes the prediction of spread through air spaces (STAS) in stage IA lung adenocarcinoma: a large-scale diagnostic study.

BACKGROUND: The preoperative prediction of spread through air spaces (STAS) in patients with early-stage lung adenocarcinoma (LUAD) is crucial for sel...

China Protocol for early screening, precise diagnosis, and individualized treatment of lung cancer.

Early screening, diagnosis, and treatment of lung cancer are pivotal in clinical practice since the tumor stage remains the most dominant factor that ...

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through mechanisms involving endoplasmic reticulum stress...

Advancing breast, lung and prostate cancer research with federated learning. A systematic review.

Federated learning (FL) is advancing cancer research by enabling privacy-preserving collaborative training of machine learning (ML) models on diverse,...

Interpretable niche-based cell‒cell communication inference using multi-view graph neural networks.

Cell‒cell communication (CCC) is a fundamental biological process for the harmonious functioning of biological systems. Increasing evidence indicates ...

Quantitative computed tomography imaging classification of cement dust-exposed patients-based Kolmogorov-Arnold networks.

BACKGROUND: Occupational health assessment is critical for detecting respiratory issues caused by harmful exposures, such as cement dust. Quantitative...

A Deep Neural Network Framework for the Detection of Bacterial Diseases from Chest X-Ray Scans.

AIMS: This research aims to develop an advanced deep-learning framework for detecting respiratory diseases, including COVID-19, pneumonia, and tubercu...

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation.

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) facilitates timely intervention. We aimed to develop a...

Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would.

INTRODUCTION: Emergency rescue scenes and pre-hospital emergency stages commonly encounter trauma victims. Life-saving measures must be taken at the s...

Screening and identification of novel protein markers of early-stage lung cancer and construction and application of screening models.

OBJECTIVE: Molecular biomarkers have the potential to improve the current state of early screening of lung cancer. This investigation aimed to identif...

Lung auscultation - today and tomorrow- a narrative review.

INTRODUCTION: Lung auscultation is a fundamental diagnostic tool for respiratory conditions. Despite advancements in medical technology, the analogue ...

Effectiveness of Digital Health Interventions for Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-Analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD), marked by dyspnea, cough, and sputum production, significantly impairs patients' quality of ...

The extent of Skeletal muscle wasting in prolonged critical illness and its association with survival: insights from a retrospective single-center study.

OBJECTIVE: Muscle wasting in critically ill patients, particularly those with prolonged hospitalization, poses a significant challenge to recovery and...