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Exploring classical machine learning for identification of pathological lung auscultations.

Computers in biology and medicine
The use of machine learning in biomedical research has surged in recent years thanks to advances in devices and artificial intelligence. Our aim is to expand this body of knowledge by applying machine learning to pulmonary auscultation signals. Despi...

Performance of Biopsy Tools in Procurement of Lung Tissue in Robot-Assisted Peripheral Navigation: A Comparison.

Respiration; international review of thoracic diseases
INTRODUCTION: Robot-assisted navigation bronchoscopy (RANB) has been gaining traction as a new technology for minimally invasive biopsies of peripheral pulmonary lesions (PPLs). Cryobiopsy is an established method of procuring satisfactory lung tissu...

Effect of da Vinci robot versus thoracoscopic surgery on lung function and oxidative stress levels in NSCLC patients: a propensity score-matched study.

Surgical endoscopy
BACKGROUND: To evaluate the short-term efficacy, lung function, and oxidative stress levels between the robotic-assisted thoracoscopic surgery (RATS) and video-assisted thoracoscopic surgery group (VATS) for non-small cell lung cancer (NSCLC).

Automatic deep learning-based pleural effusion segmentation in lung ultrasound images.

BMC medical informatics and decision making
BACKGROUND: Point-of-care lung ultrasound (LUS) allows real-time patient scanning to help diagnose pleural effusion (PE) and plan further investigation and treatment. LUS typically requires training and experience from the clinician to accurately int...

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening.

Respiratory research
OBJECTIVES: Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans ...

Analyses of Factors Associated with Acute Exacerbations of Chronic Obstructive Pulmonary Disease: A Review.

International journal of chronic obstructive pulmonary disease
Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is the exacerbation of a range of respiratory symptoms during the stable phase of chronic obstructive pulmonary disease (COPD). AECOPD is thus a dangerous stage and key event in th...

A deep learning feature extraction-based hybrid approach for detecting pediatric pneumonia in chest X-ray images.

Physical and engineering sciences in medicine
Pneumonia is a disease caused by bacteria, viruses, and fungi that settle in the alveolar sacs of the lungs and can lead to serious health complications in humans. Early detection of pneumonia is necessary for early treatment to manage and cure the d...

Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

AJR. American journal of roentgenology
Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule computer-aided detection (CAD) systems have been designed and studied primarily using adult training ...