COPD

Deep Learning-Based Diagnosis of Fatal Hypothermia Using Post-Mortem Computed Tomography.

In forensic medicine, fatal hypothermia diagnosis is not always easy because findings are not specific, especially if traumatized. Post-mortem computed tomography (PMCT) is a useful adjunct to the cause-of-death diagnosis and some qualitative image character analysis, such as diffuse hyperaeration with decreased vascularity or pulmonary emphysema, have also been utilized for fatal hypothermia. How...

Eliminating the need for manual segmentation to determine size and volume from MRI. A proof of concept on segmenting the lateral ventricles.

Manual segmentation, which is tedious, time-consuming, and operator-dependent, is currently used as the gold standard to validate automatic and semiautomatic methods that quantify geometries from 2D and 3D MR images. This study examines the accuracy of manual segmentation and generalizes a strategy to eliminate its use. Trained individuals manually measured MR lateral ventricles images of normal a...

Deep learning on graphs for multi-omics classification of COPD.

Network approaches have successfully been used to help reveal complex mechanisms of diseases including Chronic Obstructive Pulmonary Disease (COPD). H...

Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by app...

Utilization of Deep Convolutional Neural Networks for Accurate Chest X-Ray Diagnosis and Disease Detection.

Chest radiography is a widely used diagnostic imaging procedure in medical practice, which involves prompt reporting of future imaging tests and diagn...

Anti-inflammatory therapy enables robot-actuated regeneration of aged muscle.

Robot-actuated mechanical loading (ML)-based therapies ("mechanotherapies") can promote regeneration after severe skeletal muscle injury, but the effe...

Fractional Dynamics Foster Deep Learning of COPD Stage Prediction.

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. Current COPD diagnosis (i.e., spirometry) could be unrel...

Deep-learning algorithm to detect fibrosing interstitial lung disease on chest radiographs.

BACKGROUND: Antifibrotic therapies are available to treat chronic fibrosing interstitial lung diseases (CF-ILDs), including idiopathic pulmonary fibro...

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.

Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung fu...

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases.

Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. These have emerged as one of the most concerning he...

Evaluation of emphysema on thoracic low-dose CTs through attention-based multiple instance deep learning.

In addition to lung cancer, other thoracic abnormalities, such as emphysema, can be visualized within low-dose CT scans that were initially obtained i...

Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study.

Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlar...

Detection of 1-OHPyr in human urine using SERS with injection under wet liquid-liquid self-assembled films of β-CD-coated gold nanoparticles and deep learning.

1-Hydroxypyrene (1-OHPyr), a typical hydroxylated polycyclic aromatic hydrocarbon (OH-PAH), has been commonly regarded as a urinary biomarker for asse...

Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial.

Gold standard behavioral weight loss (BWL) is limited by the availability of expert clinicians and high cost of delivery. The artificial intelligence ...

Mapping the plague through natural language processing.

Pandemic diseases such as plague have produced a vast amount of literature providing information about the spatiotemporal extent, transmission, or cou...

A fully automated deep learning pipeline for micro-CT-imaging-based densitometry of lung fibrosis murine models.

Idiopathic pulmonary fibrosis, the archetype of pulmonary fibrosis (PF), is a chronic lung disease of a poor prognosis, characterized by progressively...

A Fissure-Aided Registration Approach for Automatic Pulmonary Lobe Segmentation Using Deep Learning.

The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challe...

Raman spectroscopy combined with deep learning for rapid detection of melanoma at the single cell level.

Melanoma is an aggressive and metastatic skin cancer caused by genetic mutations in melanocytes, and its incidence is increasing year by year. Underst...

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance.

The development of validated algorithms for automated handling of artifacts is essential for reliable and fast processing of EEG signals. Recently, th...

Accelerated Discovery of Ternary Gold Alloy Materials with Low Resistivity via an Interpretable Machine Learning Strategy.

New ternary gold alloys with low resistivities (ρ) were screened out via an interpretable machine learning strategy by using the support vector regres...