Pulmonology

Prognosis and prognostic factors for chronic fibrosing idiopathic interstitial pneumonias.

Progressive lung fibrosis is frequently observed in patients with idiopathic interstitial pneumonias (IIPs), especially in those with idiopathic pulmonary fibrosis (IPF) being a representative form of IIPs characterized by a poor prognosis, even in the era of antifibrotic therapy. Predicting prognosis is essential for informing patients and determining future treatment strategies. Multiple prognos...

Differentiating adenocarcinoma and squamous cell carcinoma in lung cancer using semi automated segmentation and radiomics.

INTRODUCTION: Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are frequently observed forms of non-small cell lung cancer (NSCLC), playing a significant role in global cancer mortality. This research categorizes NSCLC subtypes by analyzing image details using computer-assisted semi-automatic segmentation and radiomic features in model development.

A Machine Learning Analysis of Physiological Monitoring Signals to Detect Small Airway Narrowing Due to Cold Air Exposure in Asthma.

Asthma is a chronic inflammatory disease of the small airways, affecting over 200 million people globally. Cold air exposure is a potential risk facto...

Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens.

Mycobacteria, including (MTB) and non-tuberculosis mycobacteria (NTM), are important causes of infectious disease and cause significant mortality and...

[Incidental pulmonary nodules on CT imaging: what to do?].

Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage) lung cancers without any signs or symptoms. These...

A model developed by machine learning and principal component analysis for predicting bronchiolitis obliterans syndrome after allogeneic HSCT in a Chinese population with hematologic malignancies.

Bronchiolitis obliterans syndrome (BOS) is a severe pulmonary complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), w...

Enhancing Lung Cancer Diagnosis: An Optimization-Driven Deep Learning Approach with CT Imaging.

Lung cancer (LC) remains a leading cause of mortality worldwide, affecting individuals across all genders and age groups. Early and accurate diagnosis...

Machine Learning-Driven Discovery of TRIM Genes as Diagnostic Biomarkers for Idiopathic Pulmonary Fibrosis.

BACKGROUND Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with limited effective treatments and significant challenges in early dia...

Emergency radiology: roadmap for radiology departments.

Emergency radiology has evolved into a significant subspecialty over the past 2 decades, facing unique challenges including escalating imaging volumes...

Enhancing early mortality prediction for sepsis-associated acute respiratory distress syndrome patients via optimized machine learning algorithm: development and multiple databases' validation of the SAFE-Mo.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is associated with high mortality, with sepsis accounts for 31-34% of cases. Given the global b...

Current and future applications of artificial intelligence in lung cancer and mesothelioma.

BACKGROUND: Considerable challenges exist in managing lung cancer and mesothelioma, including diagnostic complexity, treatment stratification, early d...

Disease entity impacts muscle wasting in the ICU with COVID-19 patients losing muscle nearly twice as fast.

Muscle loss in critically ill patients, particularly during prolonged ICU stays, poses significant challenges to recovery and long-term outcomes. ICU-...

Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms.

AIMS: To study programmed death ligand 1 (PD-L1) expression and tumour infiltrating lymphocytes (TILs) in patients with early-stage non-small cell lun...

From PDMS-based exposure profiling to machine learning-predicted serum concentrations: SVOC exposure disparities across occupational and environmental scenarios.

Occupational exposure to semi-volatile organic compounds (SVOCs) among various population groups has garnered insufficient attention. We investigated ...

Accurate prediction of disease-free and overall survival in non-small cell lung cancer using patient-level multimodal weakly supervised learning.

With the rapid progress in artificial intelligence (AI) and digital pathology, prognosis prediction for non-small cell lung cancer (NSCLC) patients ha...

Can we predict the future of respiratory failure prediction?

BACKGROUND: Mortality in patients with acute respiratory failure remains high. Predicting progression of acute respiratory failure may be critical to ...

Demarcating the Development of Cirrhosis and Its Complications via Plasma Proteomic Features in an Asymptomatic Population.

The early detection of liver cirrhosis and its complications is a conundrum in clinical practice. We aim to address this conundrum using proteomic fea...

Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.

BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological pattern...

Innovative technologies and their clinical prospects for early lung cancer screening.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, due to lacking effective early-stage screening approaches. Im...

High-definition motion-resolved MRI using 3D radial kooshball acquisition and deep learning spatial-temporal 4D reconstruction.

To develop motion-resolved volumetric MRI with 1.1 mm isotropic resolution and scan times <5 min using a combination of 3D radial kooshball acquisitio...