AIMC Topic:
Databases, Factual

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Neural network-based approaches for biomedical relation classification: A review.

Journal of biomedical informatics Sep 23, 2019
The explosive growth of biomedical literature has created a rich source of knowledge, such as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in unstructured free text. Biomedical relation classification aims to ...
Medical Informatics Biomedical Research Deep Learning Natural Language Processing Neural Networks, Computer Databases, Factual Humans
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Wikidata: A large-scale collaborative ontological medical database.

Journal of biomedical informatics Sep 23, 2019
Created in October 2012, Wikidata is a large-scale, human-readable, machine-readable, multilingual, multidisciplinary, centralized, editable, structured, and linked knowledge-base with an increasing diversity of use cases. Here, we raise awareness of...
Humans Biological Ontologies Databases, Factual Electronic Health Records Multilingualism Database Management Systems Internet Semantics
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Building more accurate decision trees with the additive tree.

Proceedings of the National Academy of Sciences of the United States of America Sep 16, 2019
The expansion of machine learning to high-stakes application domains such as medicine, finance, and criminal justice, where making informed decisions requires clear understanding of the model, has increased the interest in interpretable machine learn...
Models, Statistical Decision Trees Programming Languages Machine Learning Algorithms Databases, Factual
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Supervised classification approach of biometric measures for automatic fetal defect screening in head ultrasound images.

Journal of medical engineering & technology Sep 10, 2019
This paper presents an advanced approach for foetal brain abnormalities diagnostic by integrating significant biometric features in the identification process. In foetal anomaly diagnosis, manual evaluation of foetal behaviour in ultrasound images is...
Support Vector Machine Gestational Age Brain Humans Biometry Ultrasonography Head Databases, Factual Prenatal Diagnosis Image Processing, Computer-Assisted Fetus
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SRGC-Nets: Sparse Repeated Group Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Sep 9, 2019
Group convolution is widely used in many mobile networks to remove the filter's redundancy from the channel extent. In order to further reduce the redundancy of group convolution, this article proposes a novel repeated group convolutional (RGC) kerne...
Neural Networks, Computer Databases, Factual Computers, Handheld
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Automatic detection of epileptic seizure based on approximate entropy, recurrence quantification analysis and convolutional neural networks.

Artificial intelligence in medicine Sep 7, 2019
Epilepsy is the most common neurological disorder in humans. Electroencephalogram is a prevalent tool for diagnosing the epileptic seizure activity in clinical, which provides valuable information for understanding the physiological mechanisms behind...
Databases, Factual Recurrence Sensitivity and Specificity Epilepsy Entropy Humans Electroencephalography Seizures Neural Networks, Computer Automation Algorithms
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Multi-Atlas Segmentation of Anatomical Brain Structures Using Hierarchical Hypergraph Learning.

IEEE transactions on neural networks and learning systems Sep 5, 2019
Accurate segmentation of anatomical brain structures is crucial for many neuroimaging applications, e.g., early brain development studies and the study of imaging biomarkers of neurodegenerative diseases. Although multi-atlas segmentation (MAS) has a...
Humans Neural Networks, Computer Databases, Factual Image Interpretation, Computer-Assisted Brain Deep Learning Brain Mapping
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Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

Circulation. Cardiovascular quality and outcomes Sep 5, 2019
BACKGROUND: The ECG remains the most widely used diagnostic test for characterization of cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, machine learning algorithms, and availability of large-scal...
Heart Rate Markov Chains Pattern Recognition, Automated Time Factors Electrocardiography Action Potentials Humans Predictive Value of Tests Neural Networks, Computer Signal Processing, Computer-Assisted Machine Learning Workflow Reproducibility of Results Databases, Factual Cardiovascular Diseases Prognosis Diagnosis, Computer-Assisted
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Nonpooling Convolutional Neural Network Forecasting for Seasonal Time Series With Trends.

IEEE transactions on neural networks and learning systems Sep 4, 2019
This article focuses on a problem important to automatic machine learning: the automatic processing of a nonpreprocessed time series. The convolutional neural network (CNN) is one of the most popular neural network (NN) algorithms for pattern recogni...
Time Factors Seasons Machine Learning Humans Forecasting Neural Networks, Computer Databases, Factual
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A deep learning method for image-based subject-specific local SAR assessment.

Magnetic resonance in medicine Sep 4, 2019
PURPOSE: Local specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to inclu...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Computer Simulation Reproducibility of Results Humans Male Neural Networks, Computer Healthy Volunteers Algorithms Models, Statistical Signal-To-Noise Ratio Databases, Factual Prostatic Neoplasms Phantoms, Imaging Prostate
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