COPD

New technologies in breast cancer sentinel lymph node biopsy; from the current gold standard to artificial intelligence.

Sentinel lymph node biopsy is an important diagnostic procedure performed in early breast cancer patients with clinically negative axillary lymph nodes. Detection and examination of sentinel lymph nodes determine further therapy decisions, therefore a choice of optimal technique minimising the risk of false-negative results is of great importance. Currently, the gold standard is the dual technique...

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study.

The COVID-19 pandemia due to the SARS-CoV-2 coronavirus, in its first 4 months since its outbreak, has to date reached more than 200 countries worldwide with more than 2 million confirmed cases (probably a much higher number of infected), and almost 200,000 deaths. Amplification of viral RNA by (real time) reverse transcription polymerase chain reaction (rRT-PCR) is the current gold standard test ...

Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison.

OBJECTIVE: This study determined the effect of dose reduction and kernel selection on quantifying emphysema using low-dose computed tomography (LDCT) ...

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning.

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic fi...

User-Centered Design of a Mobile Health Intervention to Enhance Exacerbation-Related Self-Management in Patients With Chronic Obstructive Pulmonary Disease (Copilot): Mixed Methods Study.

BACKGROUND: Adequate self-management skills are of great importance for patients with chronic obstructive pulmonary disease (COPD) to reduce the impac...

Pulmonary Embolism in Acute Asthma Exacerbation: Clinical Characteristics, Prediction Model and Hospital Outcomes.

PURPOSE: Little is known about the characteristics and impact of acute pulmonary embolism (PE) during episodes of asthma exacerbation. We aimed to cha...

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, econo...

Machine Learning and Prediction of All-Cause Mortality in COPD.

BACKGROUND: COPD is a leading cause of mortality.

Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed in the community. Thoracic CT scans are widely used for diagnostic and scre...

Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification.

Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indic...

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major public health problem and cause of mortality worldwide. However, COPD in the early...

Artificial intelligence and machine learning in respiratory medicine.

: The application of artificial intelligence (AI) and machine learning (ML) in medicine and in particular in respiratory medicine is an increasingly r...

Simultaneous ultra-trace quantitative colorimetric determination of antidiabetic drugs based on gold nanoparticles aggregation using multivariate calibration and neural network methods.

In this study, a simple and rapid method was investigated for the simultaneous ultra-trace colorimetric determination of Metformin (MET) and Sitaglipt...

Comparison of Artificial Intelligence-Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing.

The purpose of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for fully automated quantification of emphysema o...

Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data.

The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Inform...

A Machine-learning Approach to Forecast Aggravation Risk in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease with Clinical Indicators.

Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global Initiative for Chronic Obstructive Lung Disease (GO...

Novel biomarker genes which distinguish between smokers and chronic obstructive pulmonary disease patients with machine learning approach.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is combination of progressive lung diseases. The diagnosis of COPD is generally based on the ...

Real-time colorectal cancer diagnosis using PR-OCT with deep learning.

Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering an alternativ...

The Emerging Role of Radiomics in COPD and Lung Cancer.

Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The ...

Learning Personalized Treatment Rules from Electronic Health Records Using Topic Modeling Feature Extraction.

To address substantial heterogeneity in patient response to treatment of chronic disorders and achieve the promise of precision medicine, individualiz...