Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is tim...

A deep learning method for translating 3DCT to SPECT ventilation imaging: First comparison with Kr-gas SPECT ventilation imaging.

PURPOSE: This study aimed to evaluate the accuracy of deep learning (DL)-based computed tomography (...

A Novel Deep Learning Network and Its Application for Pulmonary Nodule Segmentation.

Pulmonary nodules are the early manifestation of lung cancer, which appear as circular shadow of no ...

A Deep-Learning-Assisted On-Mask Sensor Network for Adaptive Respiratory Monitoring.

Wearable respiratory monitoring is a fast, non-invasive, and convenient approach to provide early re...

WVALE: Weak variational autoencoder for localisation and enhancement of COVID-19 lung infections.

BACKGROUND AND OBJECTIVE: The COVID-19 pandemic is a major global health crisis of this century. The...

Robot-assisted thoracic surgery for lung cancer patients with incomplete fissure.

BACKGROUND: Robot-assisted thoracic surgery has gradually been accepted as an alternative treatment ...

HearCough: Enabling continuous cough event detection on edge computing hearables.

Cough event detection is the foundation of any measurement associated with cough, one of the primary...

Deep learning-based framework for motion-compensated image fusion in catheterization procedures.

OBJECTIVE: Augmenting X-ray (XR) fluoroscopy with 3D anatomic overlays is an essential technique to ...

A temporal dependency feature in lower dimension for lung sound signal classification.

Respiratory sounds are expressed as nonlinear and nonstationary signals, whose unpredictability make...

Prediction of lung cancer using gene expression and deep learning with KL divergence gene selection.

BACKGROUND: Lung cancer is one of the cancers with the highest mortality rate in China. With the rap...

Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve.

BACKGROUND: Due to the similar symptoms of upper airway obstruction to asthma, misdiagnosis is commo...

(De)troubling transparency: artificial intelligence (AI) for clinical applications.

Artificial intelligence (AI) and machine learning (ML) techniques occupy a prominent role in medical...

Artificial Intelligence (AI) for Lung Nodules, From the Special Series on AI Applications.

Interest in artificial intelligence (AI) applications for lung nodules continues to grow among radio...

Covariate adjustment of spirometric and smoking phenotypes: The potential of neural network models.

To increase power and minimize bias in statistical analyses, quantitative outcomes are often adjuste...

Current imaging of PE and emerging techniques: is there a role for artificial intelligence?

Acute pulmonary embolism (PE) is a critical, potentially life-threatening finding on contrast-enhanc...

Early severity prediction of BPD for premature infants from chest X-ray images using deep learning: A study at the 28th day of oxygen inhalation.

BACKGROUND AND OBJECTIVE: Bronchopulmonary dysplasia is a common respiratory disease in premature in...

S. aureus and IgE-mediated diseases: pilot or copilot? A narrative review.

INTRODUCTION: is a major opportunistic pathogen that has been implicated in the pathogenesis of sev...

Vaccine Therapy in Non-Small Cell Lung Cancer.

Immunotherapy using immune checkpoint modulators has revolutionized the oncology field, emerging as ...

An improved CNN-based architecture for automatic lung nodule classification.

Lung cancer is one of the most critical diseases due to its significant death rate compared to all o...

Incidentalomas in chest CT.

Advances in imaging technology have dramatically increased the resolution of CT and improved detecti...

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