AIMC Topic: Deep Learning

Clear Filters Showing 21141 to 21150 of 28423 articles

SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction.

Neural networks : the official journal of the International Neural Network Society
Complex network is a general model to represent the interactions within technological, social, information, and biological interaction. Often, the direct detection of the interaction relationship is costly. Thus, network structure reconstruction, the...

Detection of rice plant diseases based on deep transfer learning.

Journal of the science of food and agriculture
BACKGROUND: As the primary food for nearly half of the world's population, rice is cultivated almost all over the world, especially in Asian countries. However, the farmers and planting experts have been facing many persistent agricultural challenges...

High-throughput quantitative histology in systemic sclerosis skin disease using computer vision.

Arthritis research & therapy
BACKGROUND: Skin fibrosis is the clinical hallmark of systemic sclerosis (SSc), where collagen deposition and remodeling of the dermis occur over time. The most widely used outcome measure in SSc clinical trials is the modified Rodnan skin score (mRS...

Deep-Learning Detection of Cancer Metastases to the Brain on MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Approximately one-fourth of all cancer metastases are found in the brain. MRI is the primary technique for detection of brain metastasis, planning of radiotherapy, and the monitoring of treatment response. Progress in tumor treatment now ...

Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning.

Magnetic resonance in medicine
PURPOSE: To generate fully automated and fast 4D-flow MRI-based 3D segmentations of the aorta using deep learning for reproducible quantification of aortic flow, peak velocity, and dimensions.

Non-Standardized Patch-Based ECG Lead Together With Deep Learning Based Algorithm for Automatic Screening of Atrial Fibrillation.

IEEE journal of biomedical and health informatics
This study was to assess the feasibility of using non-standardized single-lead electrocardiogram (ECG) monitoring to automatically detect atrial fibrillation (AF) with special emphasis on the combination of deep learning based algorithm and modified ...

Prediction Model of Aryl Hydrocarbon Receptor Activation by a Novel QSAR Approach, DeepSnap-Deep Learning.

Molecules (Basel, Switzerland)
The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that senses environmental exogenous and endogenous ligands or xenobiotic chemicals. In particular, exposure of the liver to environmental metabolism-disrupting chemicals c...

Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning.

Scientific reports
Non-small cell lung cancer (NSCLC) is one of the most common lung cancers worldwide. Accurate prognostic stratification of NSCLC can become an important clinical reference when designing therapeutic strategies for cancer patients. With this clinical ...

SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning.

Genomics, proteomics & bioinformatics
Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination ...

A knowledge-driven feature learning and integration method for breast cancer diagnosis on multi-sequence MRI.

Magnetic resonance imaging
BACKGROUND: The classification of benign versus malignant breast lesions on multi-sequence Magnetic Resonance Imaging (MRI) is a challenging task since breast lesions are heterogeneous and complex. Recently, deep learning methods have been used for b...