AIMC Topic: Deep Learning

Clear Filters Showing 23611 to 23620 of 28423 articles

Automated CT segmentation for lower extremity tissues in lymphedema evaluation using deep learning.

European radiology
OBJECTIVES: Clinical assessment of lymphedema, particularly for lymphedema severity and fluid-fibrotic lesions, remains challenging with traditional methods. We aimed to develop and validate a deep learning segmentation tool for automated tissue comp...

Discovery of novel GluN1/GluN3A NMDA receptor inhibitors using a deep learning-based method.

Acta pharmacologica Sinica
Ligand-based drug discovery methods typically utilize pharmacophore similarities among molecules to screen for potential active compounds. Among these, scaffold hopping is a widely used ligand-based lead identification strategy that facilitates clini...

Deep Learning for EEG-Based Visual Classification and Reconstruction: Panorama, Trends, Challenges and Opportunities.

IEEE transactions on bio-medical engineering
Deep learning has significantly enhanced the research on the emerging issue of Electroencephalogram (EEG)-based visual classification and reconstruction, which has gained a growth of attention and concern recently. To promote the research progress, a...

nnU-Net-based high-resolution CT features quantification for interstitial lung diseases.

European radiology
OBJECTIVES: To develop a new high-resolution (HR)CT abnormalities quantification tool (CVILDES) for interstitial lung diseases (ILDs) based on the nnU-Net network structure and to determine whether the quantitative parameters derived from this new so...

Predicting treatment response to systemic therapy in advanced gallbladder cancer using multiphase enhanced CT images.

European radiology
BACKGROUND: Accurate estimation of treatment response can help clinicians identify patients who would potentially benefit from systemic therapy. This study aimed to develop and externally validate a model for predicting treatment response to systemic...

Migration of Deep Learning Models Across Ultrasound Scanners.

IEEE transactions on bio-medical engineering
A transfer function approach has recently proven effective for calibrating deep learning (DL) algorithms in quantitative ultrasound (QUS), addressing data shifts at both the acquisition and machine levels. Expanding on this approach, we develop a str...

Predicting prognosis of light-chain cardiac amyloidosis by magnetic resonance imaging and deep learning.

European heart journal. Cardiovascular Imaging
AIMS: Light-chain cardiac amyloidosis (AL-CA) is a progressive heart disease with high mortality rate and variable prognosis. The presently used Mayo staging method can only stratify patients into four stages, highlighting the necessity for a more in...

Single-image inference of clathrin-mediated endocytosis dynamics via deep learning.

The Journal of chemical physics
Clathrin-mediated endocytosis (CME) is a vital cellular process that exhibits spatial and temporal heterogeneity in its dynamics, traditionally studied through labor-intensive time-lapse microscopy and single particle tracking. To overcome the limita...