AIMC Topic: Neural Networks, Computer

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EEG-based Depression Detection Using Convolutional Neural Network with Demographic Attention Mechanism.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroencephalography (EEG)-based depression detection has become a hot topic in the development of biomedical engineering. However, the complexity and nonstationarity of EEG signals are two biggest obstacles to this application. In addition, the ge...

Emotion Recognition with Refined Labels for Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The traditional emotion classification framework usually fits all the features segments of the same trial to a fixed annotation. Considering the fact that emotion is a reaction to stimuli that lasts for varied periods, we argue that the indiscriminat...

Deep transfer learning for improving single-EEG arousal detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Datasets in sleep science present challenges for machine learning algorithms due to differences in recording setups across clinics. We investigate two deep transfer learning strategies for overcoming the channel mismatch problem for cases where two d...

Generating sequential electronic health records using dual adversarial autoencoder.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Recent studies on electronic health records (EHRs) started to learn deep generative models and synthesize a huge amount of realistic records, in order to address significant privacy issues surrounding the EHR. However, most of them only fo...

Predicting complications of diabetes mellitus using advanced machine learning algorithms.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We sought to predict if patients with type 2 diabetes mellitus (DM2) would develop 10 selected complications. Accurate prediction of complications could help with more targeted measures that would prevent or slow down their development.

Partial directed coherence based graph convolutional neural networks for driving fatigue detection.

The Review of scientific instruments
The mental state of a driver can be accurately and reliably evaluated by detecting the driver's electroencephalogram (EEG) signals. However, traditional machine learning and deep learning methods focus on the single electrode feature analysis and ign...

Polyphonic pitch tracking with deep layered learning.

The Journal of the Acoustical Society of America
This article presents a polyphonic pitch tracking system that is able to extract both framewise and note-based estimates from audio. The system uses several artificial neural networks trained individually in a deep layered learning setup. First, casc...

Frequency-dependent response in cortical network with periodic electrical stimulation.

Chaos (Woodbury, N.Y.)
Electrical stimulation can shape oscillations in brain activity. However, the mechanism of how periodic electrical stimulation modulates brain oscillations by time-delayed neural networks is poorly understood at present. To address this question, we ...

Dynamics and bifurcations in multistable 3-cell neural networks.

Chaos (Woodbury, N.Y.)
We disclose the generality of the intrinsic mechanisms underlying multistability in reciprocally inhibitory 3-cell circuits composed of simplified, low-dimensional models of oscillatory neurons, as opposed to those of a detailed Hodgkin-Huxley type [...

Deep neural networks capture texture sensitivity in V2.

Journal of vision
Deep convolutional neural networks (CNNs) trained on visual objects have shown intriguing ability to predict some response properties of visual cortical neurons. However, the factors (e.g., if the model is trained or not, receptive field size) and co...