AIMC Topic: Electroencephalography
Clear Filters Showing 1281 to 1290 of 2126 articles
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...
Post-hoc modification of linear models: Combining machine learning with domain information to make solid inferences from noisy data.
NeuroImage
Sep 26, 2019
Linear machine learning models "learn" a data transformation by being exposed to examples of input with the desired output, forming the basis for a variety of powerful techniques for analyzing neuroimaging data. However, their ability to learn the de...
Seizure Prediction in Scalp EEG Using 3D Convolutional Neural Networks With an Image-Based Approach.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 25, 2019
Epileptic seizures occur as a result of a process that develops over time and space in epileptic networks. In this study, we aim at developing a generalizable method for patient-specific seizure prediction by evaluating the spatio-temporal correlatio...
EEG-based single-channel authentication systems with optimum electrode placement for different mental activities.
Biomedical journal
Sep 24, 2019
BACKGROUND: Electroencephalogram (EEG) signals of a brain contain a unique pattern for each person and the potential for biometric applications. Authentication and security is a very important issue in our life and brainwave-based authentication is a...
Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces.
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2019
OBJECTIVE: This paper argues that Brain-Inspired Spiking Neural Network (BI-SNN) architectures can learn and reveal deep in time-space functional and structural patterns from spatio-temporal data. These patterns can be represented as deep knowledge, ...
A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
PloS one
Sep 16, 2019
Brain decoding-the process of inferring a person's momentary cognitive state from their brain activity-has enormous potential in the field of human-computer interaction. In this study we propose a zero-shot EEG-to-image brain decoding approach which ...
A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns.
IEEE journal of biomedical and health informatics
Sep 13, 2019
OBJECTIVE: We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introduced to functional network classification only very recently...
Visual Evoked Response Modulation Occurs in a Complementary Manner Under Dynamic Circuit Framework.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 12, 2019
The steady-state visual-evoked potential (SSVEP) induced by the periodic visual stimulus plays an important role in vision research. An increasing number of studies use the SSVEP to manipulate intrinsic oscillation and further regulate test performan...
Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 11, 2019
Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram (EEG) signals of patients with epilepsy, their conditions can be monito...
Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence.
Neural networks : the official journal of the International Neural Network Society
Sep 9, 2019
This paper presents a novel adaptive resonance theory (ART)-based modular architecture for unsupervised learning, namely the distributed dual vigilance fuzzy ART (DDVFA). DDVFA consists of a global ART system whose nodes are local fuzzy ART modules. ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31342
- Neural Networks, Computer 29853
- Algorithms 27004
- Deep Learning 26532
- Artificial Intelligence 24451
- Robotics 13335
- Image Processing, Computer-Assisted 9594
- Retrospective Studies 9172
- Magnetic Resonance Imaging 6218
- Reproducibility of Results 5616
- Tomography, X-Ray Computed 4799
- Support Vector Machine 4714
- Computational Biology 4279
- Brain 4061
- Computer Simulation 3896
Recent Journals
- Scientific reports 6275
- Sensors (Basel, Switzerland) 4794
- PloS one 4085
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1870
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1144
- Journal of chemical information and modeling 1021
- Nature communications 979
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 865
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 832