AIMC Topic: Neural Networks, Computer

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Is one-shot learning a viable option in drug discovery?

Expert opinion on drug discovery Mar 18, 2019
Humans Drug Discovery Drug Development Neural Networks, Computer Machine Learning
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Vector-Derived Transformation Binding: An Improved Binding Operation for Deep Symbol-Like Processing in Neural Networks.

Neural computation Mar 18, 2019
We present a new binding operation, vector-derived transformation binding (VTB), for use in vector symbolic architectures (VSA). The performance of VTB is compared to circular convolution, used in holographic reduced representations (HRRs), in terms ...
Neural Networks, Computer
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Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia.

Neural computation Mar 18, 2019
Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The neuroimaging community currently tries to take advantage of ML in order to develop an auxiliary diagnostic tool for schizophrenia diagnostics. In this...
Schizophrenia Pattern Recognition, Automated Diagnosis, Computer-Assisted Magnetic Resonance Imaging Humans Brain Male Neural Networks, Computer
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The Development of Target-Specific Machine Learning Models as Scoring Functions for Docking-Based Target Prediction.

Journal of chemical information and modeling Mar 18, 2019
The identification of possible targets for a known bioactive compound is of the utmost importance for drug design and development. Molecular docking is one possible approach for in-silico protein target prediction, whereas a molecule is docked into s...
Neural Networks, Computer Computational Biology Support Vector Machine Machine Learning Protein Conformation Molecular Docking Simulation
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Automated segmentation of the corneal endothelium in a large set of 'real-world' specular microscopy images using the U-Net architecture.

Scientific reports Mar 18, 2019
Monitoring the density of corneal endothelial cells (CEC) is essential in the management of corneal diseases. Its manual calculation is time consuming and prone to errors. U-Net, a neural network for biomedical image segmentation, has shown promising...
Cell Count Microscopy Endothelial Cells Neural Networks, Computer Image Processing, Computer-Assisted Endothelium, Corneal Humans
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Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.

Scandinavian journal of gastroenterology Mar 17, 2019
BACKGROUND AND AIM: We recently reported the role of artificial intelligence in the diagnosis of Helicobacter pylori (H. pylori) gastritis on the basis of endoscopic images. However, that study included only H. pylori-positive and -negative patients,...
Helicobacter Infections Helicobacter pylori Japan Image Processing, Computer-Assisted Gastritis Humans Endoscopy, Gastrointestinal Neural Networks, Computer
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Automatic Segmentation of the Prostate on CT Images Using Deep Neural Networks (DNN).

International journal of radiation oncology, biology, physics Mar 16, 2019
PURPOSE: Recent advances in deep neural networks (DNNs) have unlocked opportunities for their application for automatic image segmentation. We have evaluated a DNN-based algorithm for automatic segmentation of the prostate gland on a large cohort of ...
Prostatic Neoplasms Prostate Radiotherapy Planning, Computer-Assisted Retrospective Studies Male Humans Machine Learning Algorithms Neural Networks, Computer
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Exponential H∞ Filtering for Continuous-Time Switched Neural Networks Under Persistent Dwell-Time Switching Regularity.

IEEE transactions on cybernetics Mar 15, 2019
This paper focuses on the exponential H filtering issue for a class of continuous-time switched neural networks (NNs). Our aim is to design a mode-dependent filter acquiring the state of the investigated system, and ensuring the global uniform expone...
Neural Networks, Computer Algorithms Computer Simulation Time Factors
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Automatic Sleep Staging Employing Convolutional Neural Networks and Cortical Connectivity Images.

IEEE transactions on neural networks and learning systems Mar 15, 2019
Understanding of the neuroscientific sleep mechanisms is associated with mental/cognitive and physical well-being and pathological conditions. A prerequisite for further analysis is the identification of the sleep macroarchitecture through manual sle...
Adult Male Deep Learning Electroencephalography Middle Aged Algorithms Reproducibility of Results Young Adult Humans Neural Networks, Computer Electroencephalography Phase Synchronization Signal Processing, Computer-Assisted Cerebral Cortex Automation Wavelet Analysis Sleep Stages
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Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT.

European radiology Mar 15, 2019
PURPOSE: To develop a deep learning-based computer-aided diagnosis (CAD) system for use in the CT diagnosis of cervical lymph node metastasis (LNM) in patients with thyroid cancer.
Humans Area Under Curve Radiographic Image Interpretation, Computer-Assisted Neck Lymphatic Metastasis Retrospective Studies Tomography, X-Ray Computed Sensitivity and Specificity Female Male Deep Learning Diagnosis, Computer-Assisted Thyroid Neoplasms Neural Networks, Computer Algorithms
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