Pulmonology

A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event Detection.

OBJECTIVE: Obstructive sleep apnea (OSA) is diagnosed using the apnea-hypopnea index (AHI), which is the average number of respiratory events per hour of sleep. Recently, machine learning algorithms for automatic AHI assessment have been developed, but many of them do not consider the individual sleep stages or events. In this study, we aimed to develop a deep learning model to simultaneously scor...

The Past, Present, and Future Role of Artificial Intelligence in Ventilation/Perfusion Scintigraphy: A Systematic Review.

Ventilation-perfusion (V/Q) lung scans constitute one of the oldest nuclear medicine procedures, remain one of the few studies performed in the acute setting, and are amongst the few performed in the emergency setting. V/Q studies have witnessed a long fluctuation in adoption rates in parallel to continuous advances in image processing and computer vision techniques. This review provides an overvi...

Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction.

OBJECTIVES: Computed tomography (CT)-based bronchial parameters correlate with disease status. Segmentation and measurement of the bronchial lumen and...

Deformable registration of lung 3DCT images using an unsupervised heterogeneous multi-resolution neural network.

Lung image registration is more challenging than other organs. This is because the breath of the human body causes large deformations in the lung pare...

Deep learning-based classification and spatial prognosis risk score on whole-slide images of lung adenocarcinoma.

AIMS: Classification of histological patterns in lung adenocarcinoma (LUAD) is critical for clinical decision-making, especially in the early stage. H...

Pneumothorax prediction using a foraging and hunting based ant colony optimizer assisted support vector machine.

Although PNLB is generally considered safe, it is still invasive and risky. Pneumothorax, the most common complication of lung puncture, can cause sho...

Pneumonia Detection Using Enhanced Convolutional Neural Network Model on Chest X-Ray Images.

Pneumonia, caused by microorganisms, is a severely contagious disease that damages one or both the lungs of the patients. Early detection and treatmen...

Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by app...

Collaborative training of medical artificial intelligence models with non-uniform labels.

Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep learning (DL). However, building powerful and robus...

Usefulness of copper filters in digital chest radiography based on the relationship between effective detective quantum efficiency and deep learning-based segmentation accuracy of the tumor area.

This study aimed to determine the optimal radiographic conditions for detecting lesions on digital chest radiographs using an indirect conversion flat...

[Video-assisted Double-lumen Tubes in Robot-assisted Oesophageal Surgery].

Robot-assisted esophagectomies are still considered high-risk procedures requiring complex surgical and anesthesiological planning and coordination. T...

Artificial Intelligence and Interstitial Lung Disease: Diagnosis and Prognosis.

Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists, pulmonologists, and pathologists. They discuss the combin...

An expert-based system to predict population survival rate from health data.

Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends...

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia.

BACKGROUND: The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widel...

Deep learning approach for prediction and classification of potable water.

Potable water, commonly known as drinking water, refers to water that is safe to drink and does not endanger human health. It must adhere to strict qu...

Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm.

Frequent cortical arousal is associated with cardiovascular dysfunction among people with sleep-disordered breathing. Changes in heart rate variabilit...

Radiologist Worklist Reprioritization Using Artificial Intelligence: Impact on Report Turnaround Times for CTPA Examinations Positive for Acute Pulmonary Embolism.

In patients with acute pulmonary embolism (PE), timely intervention (e.g., initiation of anticoagulation) is critical for optimizing clinical outcome...

A systematic review and repeatability study on the use of deep learning for classifying and detecting tuberculosis bacilli in microscopic images.

Tuberculosis (TB) is among the leading causes of death worldwide from a single infectious agent. This disease usually affects the lungs (pulmonary TB)...

Using artificial intelligence to enhance the diagnostic accuracy of the 12-lead electrocardiogram in patients with suspected acute pulmonary embolism - Can you teach an old dog new tricks?

A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regional lung ventilation with exceptional detail with...