Pulmonology

A cascaded dual-pathway residual network for lung nodule segmentation in CT images.

It is difficult to obtain an accurate segmentation due to the variety of lung nodules in computed to...

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.

PURPOSE: Computed tomography (CT) is an effective method for detecting and characterizing lung nodul...

Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.

Exposure to certain chemicals such as disinfectants through inhalation is suspected to be involved i...

An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.

BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection...

Artificial intelligence for pulmonary function test interpretation.

Artificial intelligence for pulmonary function test interpretation.

A new technique for measuring fistula flow using venous blood gas oxygen saturation in patients with a central venous catheter.

BACKGROUND: Doppler ultrasound (DU) monitoring early after arteriovenous fistula (AVF) creation allo...

Multi-Class Neural Networks to Predict Lung Cancer.

Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate...

Deep learning facilitates the diagnosis of adult asthma.

BACKGROUND: We explored whether the use of deep learning to model combinations of symptom-physical s...

Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in ...

Tackling the Radiological Society of North America Pneumonia Detection Challenge.

We provide overviews of deep learning approaches used by two top-placing teams for the 2018 Radiolo...

Neural network model of an amphibian ventilatory central pattern generator.

The neuronal multiunit model presented here is a formal model of the central pattern generator (CPG)...

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in th...

Prediction of the five-day biochemical oxygen demand and chemical oxygen demand in natural streams using machine learning methods.

Rivers, as the most prominent component of water resources, have a key role to play in increasing th...

Detection of respiratory rate using a classifier of waves in the signal from a FBG-based vital signs sensor.

BACKGROUND AND OBJECTIVE: Monitoring of changes in respiratory rate provides information on a patien...

Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.

PURPOSE: To explore imaging biomarkers that can be used for diagnosis and prediction of pathologic s...

Water quality prediction based on recurrent neural network and improved evidence theory: a case study of Qiantang River, China.

Water quality prediction is an effective method for managing and protecting water resources by provi...

Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.

To develop a deep learning system based on 3D convolutional neural networks (CNNs), and to automatic...

Perceptions of drones, digital adherence monitoring technologies and educational videos for tuberculosis control in remote Madagascar: a mixed-method study protocol.

INTRODUCTION: Poor road and communication infrastructure pose major challenges to tuberculosis (TB) ...

Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.

BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural ne...

Importance of coding co-morbidities for APR-DRG assignment: Focus on cardiovascular and respiratory diseases.

BACKGROUND: The All Patient-Refined Diagnosis-Related Groups (APR-DRGs) system has adjusted the basi...