AIMC Topic: Deep Learning

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Automatic Seizure Detection Based on S-Transform and Deep Convolutional Neural Network.

International journal of neural systems Sep 30, 2019
Automatic seizure detection is significant for the diagnosis of epilepsy and reducing the massive workload of reviewing continuous EEGs. In this work, a novel approach, combining Stockwell transform (S-transform) with deep Convolutional Neural Networ...
Adult Sensitivity and Specificity Deep Learning Humans Cerebral Cortex Electrocorticography Epilepsy Seizures Signal Processing, Computer-Assisted
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Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.

Ophthalmology Sep 30, 2019
PURPOSE: To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SD OCT) optic nerve head images.
Diagnostic Techniques, Ophthalmological Visual Fields Visual Field Tests Optic Nerve Diseases Middle Aged Aged Optic Disk Humans Predictive Value of Tests Deep Learning Adult Glaucoma Retinal Ganglion Cells Nerve Fibers Vision Disorders Male Female
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A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.

Medical hypotheses Sep 30, 2019
Magnetic resonance imaging (MRI) images can be used to diagnose brain tumors. Thanks to these images, some methods have so far been proposed in order to distinguish between benign and malignant brain tumors. Many systems attempting to define these tu...
Humans Magnetic Resonance Imaging Deep Learning Fuzzy Logic Image Processing, Computer-Assisted Entropy Predictive Value of Tests Support Vector Machine Neural Networks, Computer Algorithms Brain Neoplasms
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A review of medical image detection for cancers in digestive system based on artificial intelligence.

Expert review of medical devices Sep 30, 2019
: At present, cancer imaging examination relies mainly on manual reading of doctors, which requests a high standard of doctors' professional skills, clinical experience, and concentration. However, the increasing amount of medical imaging data has br...
Deep Learning Humans Image Processing, Computer-Assisted Artificial Intelligence Diagnostic Imaging Machine Learning Digestive System Neoplasms
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Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library.

International journal of molecular sciences Sep 30, 2019
The constitutive androstane receptor (CAR) plays pivotal roles in drug-induced liver injury through the transcriptional regulation of drug-metabolizing enzymes and transporters. Thus, identifying regulatory factors for CAR activation is important for...
Receptors, Cytoplasmic and Nuclear Small Molecule Libraries Constitutive Androstane Receptor Deep Learning Ligands Quantitative Structure-Activity Relationship Reproducibility of Results Drug Discovery Algorithms
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Automated grading of acne vulgaris by deep learning with convolutional neural networks.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) Sep 29, 2019
BACKGROUND: The visual assessment and severity grading of acne vulgaris by physicians can be subjective, resulting in inter- and intra-observer variability.
Acne Vulgaris Photography Humans Neural Networks, Computer Algorithms Image Interpretation, Computer-Assisted Face Deep Learning Skin
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Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance.

Neural networks : the official journal of the International Neural Network Society Sep 28, 2019
In this study, we use a deep convolutional neural network (CNN) to develop a model that predicts ozone concentrations 24 h in advance. We have evaluated the model for 21 continuous ambient monitoring stations (CAMS) across Texas. The inputs for the C...
Humans Neural Networks, Computer Time Factors Ozone Meteorology Environmental Monitoring Air Pollutants Air Pollution Forecasting Wind Deep Learning
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Automated diagnosis and quantitative analysis of plus disease in retinopathy of prematurity based on deep convolutional neural networks.

Acta ophthalmologica Sep 27, 2019
BACKGROUND: The purpose of this study was to develop an automated diagnosis and quantitative analysis system for plus disease. The system provides a diagnostic decision but also performs quantitative analysis of the typical pathological features of t...
Humans Infant, Newborn Intravitreal Injections Angiogenesis Inhibitors Ranibizumab Retinopathy of Prematurity Image Interpretation, Computer-Assisted Infant, Premature Diagnosis, Computer-Assisted Retinal Vessels Deep Learning Infant, Extremely Low Birth Weight ROC Curve
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An overview and metanalysis of machine and deep learning-based CRISPR gRNA design tools.

RNA biology Sep 27, 2019
The CRISPR-Cas9 system has become the most promising and versatile tool for genetic manipulation applications. Albeit the technology has been broadly adopted by both academic and pharmaceutic societies, the activity (on-target) and specificity (off-t...
CRISPR-Cas Systems Gene Editing Gene Targeting RNA, Guide, CRISPR-Cas Systems Humans Algorithms Machine Learning Sensitivity and Specificity Deep Learning
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A deep learning framework for automatic diagnosis of unipolar depression.

International journal of medical informatics Sep 27, 2019
BACKGROUND AND PURPOSE: In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Theref...
Male Case-Control Studies Deep Learning Depressive Disorder Electroencephalography Automation Neural Networks, Computer Female Adult Humans
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