AIMC Topic: Deep Learning

Clear Filters Showing 15941 to 15950 of 28423 articles

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

The British journal of radiology
OBJECTIVE: Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to establish deep convolutional neural network (CNN) models using these two imaging mar...

The contrast-enhanced MRI can be substituted by unenhanced MRI in identifying and automatically segmenting primary nasopharyngeal carcinoma with the aid of deep learning models: An exploratory study in large-scale population of endemic area.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Administration of contrast is not desirable for all cases in clinical setting, and no consensus in sequence selection for deep learning model development has been achieved, thus we aim to explore whether contrast-enhanced m...

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers.

Scientific reports
Within the next 1.5 decades, 1 in 7 U.S. adults is anticipated to suffer from age-related macular degeneration (AMD), a degenerative retinal disease which leads to blindness if untreated. Optical coherence tomography angiography (OCTA) has become a p...

Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records.

BMC medical informatics and decision making
PURPOSE: Predictively diagnosing infectious diseases helps in providing better treatment and enhances the prevention and control of such diseases. This study uses actual data from a hospital. A multiple infectious disease diagnostic model (MIDDM) is ...

Deep learning fetal ultrasound video model match human observers in biometric measurements.

Physics in medicine and biology
This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, biparietal diameter, abdominal circumference and femur length, and to estimate gestati...

Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model.

Journal of healthcare engineering
Glaucoma is the second most common cause for blindness around the world and the third most common in Europe and the USA. Around 78 million people are presently living with glaucoma (2020). It is expected that 111.8 million people will have glaucoma b...

Improving Automatic Control of Upper-Limb Prosthesis Wrists Using Gaze-Centered Eye Tracking and Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Many upper-limb prostheses lack proper wrist rotation functionality, leading to users performing poor compensatory strategies, leading to overuse or abandonment. In this study, we investigate the validity of creating and implementing a data-driven pr...

Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Background parenchymal enhancement (BPE) is assessed on breast MRI reports as mandated by the Breast Imaging Reporting and Data System (BI-RADS) but is prone to inter and intrareader variation. Semiautomated and fully automated BPE assess...

A deep learning-based system capable of detecting pneumothorax via electrocardiogram.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: To determine if an electrocardiogram-based artificial intelligence system can identify pneumothorax prior to radiological examination.