Pulmonology

Comprehensive anatomic ontologies for lung development: A comparison of alveolar formation and maturation within mouse and human lung.

BACKGROUND: Although the mouse is widely used to model human lung development, function, and disease...

Excitation Emission Matrix Fluorescence Spectroscopy for Combustion Generated Particulate Matter Source Identification.

The inhalation of particulate matter (PM) is a significant health risk associated with reduced life ...

Machine Learning Reveals the Texture of Regional Lung Ventilation at CT.

Chronic Obstructive Pulmonary Disease: Thoracic CT Texture Analysis and Machine Learning to Predict Pulmonary Ventilation.

Background Fixed airflow limitation and ventilation heterogeneity are common in chronic obstructive ...

Use of pressure-regulated volume control in the first 48 hours of hospitalization of mechanically ventilated patients with sepsis or septic shock, with or without ARDS.

PURPOSE: To evaluate the impact of pressure-regulated volume control (PRVC/VC+) use on delivered tid...

Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.

INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall s...

Dehydroepiandrosterone Supplementation May Benefit Women with Asthma Who Have Low Androgen Levels: A Pilot Study.

INTRODUCTION: Among individuals with severe asthma, FEV is low in individuals with low dehydroepiand...

Effect of dexmedetomidine sedation on swallowing reflex: A pilot study.

BACKGROUND/PURPOSE: Swallowing reflex depression during dental treatment or oral surgery may cause w...

Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems.

Deep learning (DL) neural networks have only recently been employed to interpret chest radiography (...

Deep learning to stratify lung nodules on annual follow-up CT.

Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method.

BACKGROUND: Current lung cancer screening guidelines use mean diameter, volume or density of the lar...

Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.

BACKGROUND: The differential diagnosis of tuberculous pleural effusion (TPE) is challenging. In rece...

MR-Forest: A Deep Decision Framework for False Positive Reduction in Pulmonary Nodule Detection.

With the development of deep learning methods such as convolutional neural network (CNN), the accura...

Outpatient Anesthesia Facilitates Stereotactic Body Radiation Therapy for Early Stage Lung Cancer Patients With Advanced Cognitive Impairments.

PURPOSE: To report on the use of outpatient anesthesia (OPA) facilitating delivery of stereotactic b...

Rapid multiplex microfiber-based immunoassay for anti-MERS-CoV antibody detection.

On-site multiplex biosensors for innate immunity antibodies are ideal tools for monitoring health st...

A comparative study of machine learning classifiers for risk prediction of asthma disease.

Asthma is a chronic disease characterized by wheezing, chest tightening and difficulty in breathing ...

A New Multimodel Machine Learning Framework to Improve Hepatic Fibrosis Grading Using Ultrasound Elastography Systems from Different Vendors.

The purpose of the work described here was to determine if the diagnostic performance of point and 2...

ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis.

PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU...

DeepBranch: Deep Neural Networks for Branch Point Detection in Biomedical Images.

Morphology reconstruction of tree-like structures in volumetric images, such as neurons, retinal blo...

Machine Learning Approach for Prediction of Hematic Parameters in Hemodialysis Patients.

This paper shows the application of machine learning techniques to predict hematic parameters using...

Predicting post-stroke pneumonia using deep neural network approaches.

BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length...