Pulmonology

Diagnostic accuracy of a commercially available, deep learning-based chest X-ray interpretation software for detecting culture-confirmed pulmonary tuberculosis.

BACKGROUND: Few evaluations of computer-aided detection (CAD) software for analyzing chest radiographs for tuberculosis have used mycobacterial culture as the reference standard.

Prediction of Bronchopneumonia Inpatients' Total Hospitalization Expenses Based on BP Neural Network and Support Vector Machine Models.

OBJECTIVE: BP neural network (BPNN) model and support vector machine (SVM) model were used to predict the total hospitalization expenses of patients with bronchopneumonia.

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 time consuming, is subjective, requires training, and...

Deep Learning Assessment of Emphysema Progression at CT Predicts Outcomes.

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 (CT) ventilation imaging (CTVI).

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study.

This retrospective study aimed to develop and validate a deep learning model for the classification of coronavirus disease-2019 (COVID-19) pneumonia, ...

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 more than 3 cm on the computed tomography (CT) ima...

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 recognition of human health abnormalities like restr...

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

BACKGROUND: Robot-assisted thoracic surgery has gradually been accepted as an alternative treatment for early-stage non-small-cell lung cancer (NSCLC)...

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 symptoms of pulmonary illnesses. This paper propo...

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 improve the guidance of the catheterization proced...

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 rapid development of high-throughput sequencing techn...

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

Respiratory sounds are expressed as nonlinear and nonstationary signals, whose unpredictability makes it difficult to extract significant features for...

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 common. Spirometry is a cost-effective screening test f...

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

Artificial intelligence (AI) and machine learning (ML) techniques occupy a prominent role in medical research in terms of the innovation and developme...

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 radiologists, particularly with the expanding eligibili...

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 adjusted for precision and confounding variables using st...

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-enhanced cross-sectional chest imaging. Timely and accur...

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 infants. The severity is diagnosed at the 56th day a...

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 several chronic inflammatory diseases including bronc...