COPD

Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "multiclass machine learning (MCML)-based algorithms" (labelled as AtheroEdge 3.0) and assess whether considering carotid ultrasound imaging fused with ...

Development and evaluation of a deep learning based artificial intelligence for automatic identification of gold fiducial markers in an MRI-only prostate radiotherapy workflow.

Identification of prostate gold fiducial markers in magnetic resonance imaging (MRI) images is challenging when CT images are not available, due to misclassifications from intra-prostatic calcifications. It is also a time consuming task and automated identification methods have been suggested as an improvement for both objectives. Multi-echo gradient echo (MEGRE) images have been utilized for manu...

Neuromorphic on-chip recognition of saliva samples of COPD and healthy controls using memristive devices.

Chronic Obstructive Pulmonary Disease (COPD) is a life-threatening lung disease, affecting millions of people worldwide. Implementation of Machine Lea...

A Model Using Support Vector Machines Recursive Feature Elimination (SVM-RFE) Algorithm to Classify Whether COPD Patients Have Been Continuously Managed According to GOLD Guidelines.

PURPOSE: Patients with chronic obstructive pulmonary disease (COPD) would have a poor prognosis if they were not continuously managed according to the...

Predictive diagnosis of chronic obstructive pulmonary disease using serum metabolic biomarkers and least-squares support vector machine.

OBJECTIVE: Development of biofluid-based biomarkers is attractive for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking....

Ligand-protected gold/silver superatoms: current status and emerging trends.

Monolayer-protected gold/silver clusters have attracted much interest as nano-scale building units for novel functional materials owing to their nonbu...

Identification of exacerbation risk in patients with liver dysfunction using machine learning algorithms.

The prediction of the liver failure (LF) and its proper diagnosis would lead to a reduction in the complications of the disease and prevents the progr...

Claims-Based Algorithms for Identifying Patients With Pulmonary Hypertension: A Comparison of Decision Rules and Machine-Learning Approaches.

Background Real-world healthcare data are an important resource for epidemiologic research. However, accurate identification of patient cohorts-a cruc...

Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer.

Manual segmentation is the gold standard method for radiation therapy planning; however, it is time-consuming and prone to inter- and intra-observer v...

Successful Treatment of Allergic Bronchopulmonary Aspergillosis Using a Combination of Inhaled Fluticasone Furoate/Vilanterol and Oral Voriconazole.

Systemic corticosteroids are considered to be the standard treatment for allergic bronchopulmonary aspergillosis (ABPA). However, there is controversy...

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical trials, is increasingly recognized as an opportunity ...

Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.

Treatment planning for pancreas stereotactic body radiation therapy (SBRT) is a difficult and time-consuming task. In this study, we aim to develop a...

CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions.

Cardiac CINE magnetic resonance imaging is the gold-standard for the assessment of cardiac function. Imaging accelerations have shown to enable 3D CIN...

Investigation of the Dose-Enhancement Effects of Spherical and Rod-Shaped Gold Nanoparticles on the HeLa Cell Line.

BACKGROUND: Cervical cancer cells are known as radioresistant cells. Current treatment methods have not improved the patients' survival efficiently; t...

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides.

Exercise-induced pulmonary hemorrhage (EIPH) is a common condition in sport horses with negative impact on performance. Cytology of bronchoalveolar la...

Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study.

BACKGROUND: Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patie...

COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda.

Chronic Obstructive Pulmonary Disease (COPD) is a highly heterogeneous condition projected to become the third leading cause of death worldwide by 203...

DCT-MIL: Deep CNN transferred multiple instance learning for COPD identification using CT images.

While many pre-defined computed tomographic (CT) measures have been utilized to characterize chronic obstructive pulmonary disease (COPD), it is still...

[Technological Innovations in Pulmonology - Examples from Diagnostics and Therapy].

A significant proportion of the current technological developments in pneumology originate from the various areas of information technology. The spect...

Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease.

BACKGROUNDCurrently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow ob...