Pulmonology

Prediction of favorable outcomes of acute basilar artery occlusion using machine learning.

BACKGROUND: This study aims to develop an interpretable machine learning model using SHapley Additive exPlanations (SHAP) to predict favorable outcomes based on clinical, imaging, and angiographic data. METHODS: This study analyzed data from 184 patients with acute basilar artery occlusion (BAO) who underwent endovascular treatment (EVT) and completed a 90-day follow-up at Shanxi Provincial People...

Assessing the influence of kernel selection on chest computed tomography image quality across varying dose levels using TrueFidelity reconstruction.

Deep learning image reconstruction (DLIR) utilizes neural networks to generate high-quality computed tomography (CT) images. One commercially available DLIR software is TrueFidelity from GE Healthcare. The Standard kernel was the only available reconstruction kernel previously, but recently other kernels, including the Lung kernel, have been introduced by GE. This study aimed to evaluate the image...

Improving visibility of small anatomical details on low and ultra-low dose computed tomography with artificial intelligence-based image reconstructions.

To assess how computed tomography (CT) image reconstruction techniques affect perceived diagnostic image quality at varying radiation dose levels in c...

Acid-Base Status During Venoarterial Extracorporeal Membrane Oxygenator Support in Patients With Cardiogenic Shock.

BACKGROUND: The prognostic significance of an adverse acid-base milieu despite venoarterial extracorporeal membrane oxygenation support in patients wi...

Machine learning diagnostic framework for liver fibrosis in chronic hepatitis B based on routine laboratory tests.

Early detection of liver fibrosis in chronic hepatitis B (CHB) patients is crucial for improving their prognosis. This study aims to develop a machine...

Functional-based multi-omics early prediction of radiation pneumonitis in NSCLC using AI-generated perfusion and ventilation from planning CT.

ObjectiveThis study aims to develop a functional-based multi-omics model for early prediction of radiation pneumonitis (RP) by extracting radiomic and...

[Care for uncontrolled asthma in Germany - with focus on Magdeburg and Mannheim regions].

Description of treatment and prescription patterns among asthma patients in the regions of Magdeburg (MD) and Mannheim (MA) compared nationwide.We ana...

Lung cancer as a global health challenge: Multidimensional biomarker research and therapeutic advances.

Lung cancer, the leading cause of global cancer-related mortality, is categorized into small-cell and non-small-cell subtypes. The heterogeneous non-s...

Bayesian networks for predicting clinical outcomes in COVID-19 patients: A retrospective study in a resource-limited setting.

BACKGROUND: The COVID-19 pandemic has highlighted the critical need for robust, interpretable predictive models to guide clinical decision-making for ...

Idiopathic pulmonary fibrosis from a multiscale mechanobiology perspective: Mechanisms and future therapeutic prospects.

Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease that induces irreversible fibrosis and architectural remodeling. Traditional ...

Enhanced pneumonia prognosis via a hybrid deep learning ensemble: Dense Net, Efficient Net, and VGG16 integration.

Pneumonia, a prevalent and potentially life-threatening lung infection, requires rapid and precise diagnosis for effective treatment. Conventional cli...

Based on WGCNA and machine learning studies, SMURF2 drives NSCLC malignant transformation, ferroptosis, and macrophage polarization by ubiquitinating SPP1.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with poor prognosis and high mortality in advanced stages. Although sec...

AI in the Prediction of Hepatic Fibrosis Progression Using Non-Coding RNAs.

Hepatic fibrosis is a dynamic and progressive condition that can lead to cirrhosis and hepatocellular carcinoma (HCC) if left untreated. Appropriate a...

Evolutionary-Based Deep Learning Network Model using Adaptive Mixing Differential Evolution and Application in Acute Pulmonary Embolism.

INTRODUCTION: Acute pulmonary embolism (APE) is characterized by high incidence and mortality, along with non-specific clinical manifestations. Its co...

[Expert consensus on the clinical application of robotic-assisted bronchoscopy].

Robotic-assisted bronchoscopy (RAB) is an emerging diagnostic and interventional technology which integrates thin-slice CT-based virtual airway recons...

Machine learning-based prediction of high hospital charges after lung transplantation in chronic obstructive pulmonary disease patients.

Detection of Lung and Colon Cancer Using XRx-Net With Histopathological Images.

Lung and Colon Cancer (LCC) is a prevalent type of cancer influenced by factors such as genetics, smoking, second-hand smoke exposure, and alcohol con...

Association between air pollution exposure and multimorbidity among middle-aged and older adults in China: a cross-sectional study.

As the world's population ages, multimorbidity is becoming an increasingly significant burden in the elderly population. Environmental exposures, part...

Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma.

BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which ca...

Comparative Performance of 3 Artificial Intelligence Systems for Lung Nodule Characterization in Low-Dose Computed Tomography Screening.

PURPOSE: This study evaluates 3 artificial intelligence (AI) systems in detecting, characterizing, and classifying lung nodules on low-dose computed t...