COPD

Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China.

Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of input features in the complex system of environmental stressors - mental disorders (MDs), especially for exposure to air pollution mixture. In this stu...

Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease.

Heterogeneous clinical manifestations and progression of chronic obstructive pulmonary disease (COPD) affect patient health risk assessment, stratification, and management. Pulmonary function tests are used to diagnose and classify the severity of COPD, but they cannot fully represent the type or range of pathophysiologic abnormalities of the disease. To evaluate whether deep radiomics from chest ...

Automated cortical thickness measurement of the mandibular condyle head on CBCT images using a deep learning method.

This study proposes a deep learning model for cortical bone segmentation in the mandibular condyle head using cone-beam computed tomography (CBCT) and...

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, a...

A model of modified -iodobenzylguanidine conjugated gold nanoparticles for neuroblastoma treatment.

Iodine-131 -iodobenzylguanidine (I-IBG) has been utilized as a standard treatment to minimize adverse side effects by targeting therapies to bind to t...

Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The dis...

Nylon membranes modified by gold nanoparticles as surface-enhanced Raman spectroscopy substrates for several pesticides detection.

Surface enhanced Raman spectroscopy (SERS) is an attractive means for trace compound detection because of its high sensitivity, however, the poor repr...

Development of novel-nanobody-based lateral-flow immunochromatographic strip test for rapid detection of recombinant human interferon α2b.

Recombinant human interferon α2b (rhIFNα2b) is widely used as an antiviral therapy agent for the treatment of hepatitis B and hepatitis C. The current...

The cardiovascular phenotype of Chronic Obstructive Pulmonary Disease (COPD): Applying machine learning to the prediction of cardiovascular comorbidities.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous group of lung conditions that are challenging to diagnose and treat. As th...

Green synthesis and characterization of gold nanoparticles and their application for the rapid detection of glycyrrhizin with immunochromatographic strips.

In this study, a facile and environmentally friendly synthesis process was proposed without regular chemical additives. We successfully synthesized sp...

AI-based monitoring of retinal fluid in disease activity and under therapy.

Retinal fluid as the major biomarker in exudative macular disease is accurately visualized by high-resolution three-dimensional optical coherence tomo...

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of bacterial infections because its concentration inc...

Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.

An objective measure of pain remains an unmet need of people with chronic pain, estimated to be 1/3 of the adult population in the United States. The ...

A deep learning approach to gold nanoparticle quantification in computed tomography.

INTRODUCTION: Deep learning (DL) is used to classify, detect, and quantify gold nanoparticles (AuNPs) in a human-sized phantom with a clinical MDCT sc...

Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.

Chronic airway diseases are characterized by airway inflammation, obstruction, and remodeling and show high prevalence, especially in developing count...

A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation.

OBJECTIVE: At present, there is no consensus on the best strategy for interpreting the cardiopulmonary exercise test's (CPET) results. This study is a...

A Generative Adversarial Network (GAN) Technique for Internet of Medical Things Data.

The application of machine learning and artificial intelligence techniques in the medical world is growing, with a range of purposes: from the identif...

Automatic pulmonary vessel segmentation on noncontrast chest CT: deep learning algorithm developed using spatiotemporally matched virtual noncontrast images and low-keV contrast-enhanced vessel maps.

OBJECTIVES: To develop a deep learning-based pulmonary vessel segmentation algorithm (DLVS) from noncontrast chest CT and to investigate its clinical ...

Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study.

BACKGROUND: The World Health Organization has projected that by 2030, chronic obstructive pulmonary disease (COPD) will be the third-leading cause of ...

Network of gold conjugates for enhanced sensitive immunochromatographic assays of troponins.

Highly sensitive detection of cardiac troponins I and T (cTnI and cTnT) was completed by immunochromatography with double amplification, through the b...