Pulmonology

Study on transfer learning capabilities for pneumonia classification in chest-x-rays images.

BACKGROUND: over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of screening tools with high diagnostic accuracy for new illnesses such as COVID-19. In that regard, deep learning approaches have proven as effective solutions for pneumonia classification, especially when considering chest-x-rays images. However, this ...

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future exacerbation to allow targeted prevention measures. We sought to evaluate the utility of models using spatiotemporally resolved climatic data and indiv...

Deep learning for spirometry quality assurance with spirometric indices and curves.

BACKGROUND: Spirometry quality assurance is a challenging task across levels of healthcare tiers, especially in primary care. Deep learning may serve ...

MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data.

PURPOSE: Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, devel...

Automated estimation of total lung volume using chest radiographs and deep learning.

BACKGROUND: Total lung volume is an important quantitative biomarker and is used for the assessment of restrictive lung diseases.

A Principal Neighborhood Aggregation-Based Graph Convolutional Network for Pneumonia Detection.

Pneumonia is one of the main causes of child mortality in the world and has been reported by the World Health Organization (WHO) to be the cause of on...

COVID Detection From Chest X-Ray Images Using Multi-Scale Attention.

Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (c...

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for ...

Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models.

Coronavirus 2019 (COVID-19) is a highly transmissible and pathogenic virus caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), which fir...

Robot-assisted minimally invasive esophagectomy (RAMIE) with side-to-side semi-mechanical anastomosis: analysis of a learning curve.

Minimally invasive esophagectomy (MIE) reduces mortality and morbidity related to esophageal surgery, but a long learning curve is necessary due to th...

Evolution and Neural Network Prediction of CO Emissions in Weaned Piglet Farms.

This paper aims to study the evolution of CO concentrations and emissions on a conventional farm with weaned piglets between 6.9 and 17.0 kg live weig...

3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility.

This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory phases with a lung tumor and predict the lung tumo...

Deep Learning-Based Automatic CT Quantification of Coronavirus Disease 2019 Pneumonia: An International Collaborative Study.

OBJECTIVE: We aimed to develop and validate the automatic quantification of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) ...

Predicting Usual Interstitial Pneumonia Histopathology From Chest CT Imaging With Deep Learning.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal form of interstitial lung disease (ILD) characterized by the absence of ...

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic within a short time. Reverse transcription-polymer...

Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization.

OBJECTIVE: Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. T...

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiolog...

Single utility port approach in robot-assisted sleeve segmentectomy for bronchial carcinoid tumor.

Bronchial carcinoid tumors are low-grade malignant and lung-sparing surgery is preferred for the removal of these tumors. We describe a surgical techn...

A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.

PURPOSE: We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT...

An Interpretable Chest CT Deep Learning Algorithm for Quantification of COVID-19 Lung Disease and Prediction of Inpatient Morbidity and Mortality.

RATIONALE AND OBJECTIVES: The burden of coronavirus disease 2019 (COVID-19) airspace opacities is time consuming and challenging to quantify on comput...