AIMC Topic:
Databases, Factual

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A Novel Deep Neural Network for Robust Detection of Seizures Using EEG Signals.

Computational and mathematical methods in medicine Apr 7, 2020
The detection of recorded epileptic seizure activity in electroencephalogram (EEG) segments is crucial for the classification of seizures. Manual recognition is a time-consuming and laborious process that places a heavy burden on neurologists, and he...
Models, Neurological Databases, Factual Humans Diagnosis, Computer-Assisted Neural Networks, Computer Models, Statistical Deep Learning Algorithms Electroencephalography Computational Biology Seizures Signal Processing, Computer-Assisted Nonlinear Dynamics
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Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks.

Physical and engineering sciences in medicine Apr 3, 2020
In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection of the Coronavirus disease. The aim of the study is to evaluate the per...
Neural Networks, Computer Pandemics COVID-19 Databases, Factual Humans Pneumonia, Viral SARS-CoV-2 Deep Learning Coronavirus Infections Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Pneumonia, Bacterial Betacoronavirus
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A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Apr 1, 2020
Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning algorithm that could predict individual cell immunophenotype based on hematoxylin and eosin (H&E) staining would save money, time, and reduce tissue co...
Immunohistochemistry Melanocytes SOXE Transcription Factors Databases, Factual Melanoma Skin Neoplasms Staining and Labeling Humans Neural Networks, Computer Machine Learning Algorithms
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A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo, Egypt.

International journal of injury control and safety promotion Apr 1, 2020
The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequentl...
Adult Male Middle Aged Adolescent Databases, Factual Humans Quality Improvement Female Machine Learning Triage Wounds and Injuries Young Adult Trauma Severity Indices Egypt Occupational Injuries Accidents, Traffic
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Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society Apr 1, 2020
Convolutional neural networks (CNNs), a popular type of deep neural network, have been actively applied to image recognition, object detection, object localization, semantic segmentation, and object instance segmentation. Accordingly, the applicabili...
Humans Neural Networks, Computer Databases, Factual Otitis Media Tympanic Membrane Neuroendoscopy Reproducibility of Results Deep Learning ROC Curve
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Multi-view projected clustering with graph learning.

Neural networks : the official journal of the International Neural Network Society Apr 1, 2020
Graph based multi-view learning is well known due to its effectiveness and good clustering performance. However, most existing methods directly construct graph from original high-dimensional data which always contain redundancy, noise and outlying en...
Machine Learning Algorithms Databases, Factual Cluster Analysis
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Chronic gastritis classification using gastric X-ray images with a semi-supervised learning method based on tri-training.

Medical & biological engineering & computing Mar 27, 2020
High-quality annotations for medical images are always costly and scarce. Many applications of deep learning in the field of medical image analysis face the problem of insufficient annotated data. In this paper, we present a semi-supervised learning ...
Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Chronic Disease Radiography Humans Neural Networks, Computer Databases, Factual Gastritis Supervised Machine Learning
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A Smartphone Lightweight Method for Human Activity Recognition Based on Information Theory.

Sensors (Basel, Switzerland) Mar 27, 2020
Smartphones have emerged as a revolutionary technology for monitoring everyday life, and they have played an important role in Human Activity Recognition (HAR) due to its ubiquity. The sensors embedded in these devices allows recognizing human behavi...
Algorithms Databases, Factual Smartphone Monitoring, Physiologic Accelerometry Human Activities Humans Information Theory Machine Learning
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Multi-way backpropagation for training compact deep neural networks.

Neural networks : the official journal of the International Neural Network Society Mar 26, 2020
Depth is one of the key factors behind the success of convolutional neural networks (CNNs). Since ResNet (He et al., 2016), we are able to train very deep CNNs as the gradient vanishing issue has been largely addressed by the introduction of skip con...
Data Compression Neural Networks, Computer Databases, Factual Pattern Recognition, Automated Humans
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Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis: a case-control development and validation study.

The Lancet. Digital health Mar 26, 2020
BACKGROUND: Many individuals who will experience a first episode of psychosis (FEP) are not detected before occurrence, limiting the effect of preventive interventions. The combination of machine-learning methods and electronic health records (EHRs) ...
Area Under Curve Psychotic Disorders Humans Models, Biological Datasets as Topic Neural Networks, Computer Schizophrenia Machine Learning Retrospective Studies Data Analysis Male Delivery of Health Care Case-Control Studies Electronic Health Records Middle Aged Databases, Factual Cohort Studies Female Risk Assessment Prognosis Adult ROC Curve Data Management
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