COPD

Correlation of the modified Medical Research Council dyspnea scale with airway structure assessed by three-dimensional CT in patients with chronic obstructive pulmonary disease.

BACKGROUND: Dyspnea is a common symptom in chronic obstructive pulmonary disease (COPD). The modified Medical Research Council (mMRC) dyspnea scale is a widely used questionnaire to assess dyspnea. However, the relationship of the mMRC dyspnea scale with morphological airway structures in COPD remains unclear. We evaluated the correlation between the mMRC dyspnea scale and imaging-based airway str...

SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network.

Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-invasively. We recorded 10 second-300 frame fingertip videos using a smartphone in 75 adults. Red, green, and blue pixel intensities were estimated for ea...

Polyelectrolyte-Coated Gold Nanoparticles: The Effect of Salt and Polyelectrolyte Concentration on Colloidal Stability.

Gold nanoparticles are widely used in biomedical applications. Their ease of surface modification, biocompatibility and the presence of surface plasmo...

A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospi...

Pulmonary Function Testing in Elderly Patients Treated for a Myasthenia Gravis Exacerbation.

BACKGROUND AND PURPOSE: Pulmonary function testing is a standard part of care for patients admitted to hospital with a myasthenia gravis exacerbation....

Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life...

Molecular prevalence of parvovirus B19 among HIV1-infected patients in Iran.

Different outcomes of parvovirus B19 (B19V) infection in immunocompromised patients, including HIV1-infected persons, may be life-threatening. Consid...

A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography.

OBJECTIVES:: The distal root of the mandibular first molar occasionally has an extra root, which can directly affect the outcome of endodontic therapy...

Identification of Novel Genes in Human Airway Epithelial Cells associated with Chronic Obstructive Pulmonary Disease (COPD) using Machine-Based Learning Algorithms.

The aim of this project was to identify candidate novel therapeutic targets to facilitate the treatment of COPD using machine-based learning (ML) algo...

Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net.

We propose a novel airway segmentation method in volumetric chest computed tomography (CT) and evaluate its performance on multiple datasets. The segm...

Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video).

BACKGROUND AND AIMS: In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic muc...

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.

BACKGROUND: Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disea...

Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We sys...

Small airway segmentation in thoracic computed tomography scans: a machine learning approach.

Small airway obstruction is a main cause for chronic obstructive pulmonary disease (COPD). We propose a novel method based on machine learning to extr...

Automatic extraction of gene-disease associations from literature using joint ensemble learning.

A wealth of knowledge concerning relations between genes and its associated diseases is present in biomedical literature. Mining these biological asso...

Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED.

OBJECTIVE: The prediction of emergency department (ED) disposition at triage remains challenging. Machine learning approaches may enhance prediction. ...

Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.

Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this g...

Using Robots at Home to Support Patients With Chronic Obstructive Pulmonary Disease: Pilot Randomized Controlled Trial.

BACKGROUND: Socially assistive robots are being developed for patients to help manage chronic health conditions such as chronic obstructive pulmonary ...

Mixed Th2 and non-Th2 inflammatory pattern in the asthma-COPD overlap: a network approach.

INTRODUCTION: The asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is a clinical condition that combines features of those two diseas...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The ...