Pulmonology

MARnet: multi-scale adaptive residual neural network for chest X-ray images recognition of lung diseases.

Chest X-ray image is an important clinical diagnostic reference to lung diseases that is a serious threat to human health. At present, with the rapid development of computer vision and deep learning technology, many scholars have carried out the fruitful research on how to build a valid model for chest X-ray images recognition of lung diseases. While some efforts are still expected to improve the ...

A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma.

OBJECTIVE: To develop and validate a deep learning nomogram (DLN) model constructed from non-contrast computed tomography (CT) images for discriminating minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma (IAC) in patients with subsolid pulmonary nodules (SSPNs).

Non-Contact Spirometry Using a Mobile Thermal Camera and AI Regression.

Non-contact physiological measurements have been under investigation for many years, and among these measurements is non-contact spirometry, which cou...

An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model.

Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing river water quality. Artificial intelligence (AI) methods have...

Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans.

Deep learning (DL) is a breakthrough technology for medical imaging with high sample size requirements and interpretability issues. Using a pretrained...

Artificial Intelligence Assessment of Renal Scarring (AIRS Study).

BACKGROUND: The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification...

Reader Perceptions and Impact of AI on CT Assessment of Air Trapping.

Quantitative imaging measurements can be facilitated by artificial intelligence (AI) algorithms, but how they might impact decision-making and be perc...

An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis.

Tuberculosis (TB) is the greatest irresistible illness in humans, caused by microbes Mycobacterium TB (MTB) bacteria and is an infectious disease that...

Robotic, totally endoscopic atrial septal defect repair.

Atrial septal defect accounts for 10-15% of congenital heart disease cases. Small-diameter atrial septal defects diagnosed during infancy or early adu...

A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.

BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration...

Computational methods directed towards drug repurposing for COVID-19: advantages and limitations.

Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available agains...

Bacterial coinfections with coronavirus disease 2019 (COVID-19).

BACKGROUND: The pandemic caused by severe acute respiratory coronavirus virus 2 (SARS-CoV-2) has dramatically increased cheshospitalizations, and it i...

Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.

BACKGROUND: Artificial intelligence (AI) has the potential to personalise mechanical ventilation strategies for patients with respiratory failure. How...

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is ...

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.

INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postn...

Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.

Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to brea...

Using infrared imaging and deep learning in fit-checking of respiratory protective devices among healthcare professionals.

AIMS: This study aimed to investigate the application of infrared thermal imaging and adopt deep learning to detect air leakage for determining the fi...

Machine learning implicates the IL-18 signaling axis in severe asthma.

Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has ...

Design of lung nodules segmentation and recognition algorithm based on deep learning.

BACKGROUND: Accurate segmentation and recognition algorithm of lung nodules has great important value of reference for early diagnosis of lung cancer....

A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.

Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually le...