AIMC Topic: Humans

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Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases.

Artificial intelligence in medicine
In order to gain insight into oligogenic disorders, understanding those involving bi-locus variant combinations appears to be key. In prior work, we showed that features at multiple biological scales can already be used to discriminate among two type...

An Improved Full Convolutional Network Combined with Conditional Random Fields for Brain MR Image Segmentation Algorithm and its 3D Visualization Analysis.

Journal of medical systems
Existing brain region segmentation algorithms based on deep convolutional neural networks (CNN) are inefficient for object boundary segmentation. In order to enhance the segmentation accuracy of brain tissue, this paper proposed an object region segm...

Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback.

Journal of neuroengineering and rehabilitation
BACKGROUND: Add-on robot-mediated therapy has proven to be more effective than conventional therapy alone in post-stroke gait rehabilitation. Such robot-mediated interventions routinely use also visual biofeedback tools. A better understanding of bio...

Hybrid scattering-LSTM networks for automated detection of sleep arousals.

Physiological measurement
OBJECTIVE: Early detection of sleep arousal in polysomnographic (PSG) signals is crucial for monitoring or diagnosing sleep disorders and reducing the risk of further complications, including heart disease and blood pressure fluctuations.

Maximal flexibility in dynamic functional connectivity with critical dynamics revealed by fMRI data analysis and brain network modelling.

Journal of neural engineering
OBJECTIVE: The exploration of time-varying functional connectivity (FC) through human neuroimaging techniques provides important new insights on the spatio-temporal organization of functional communication in the brain's networks and its alterations ...

SpikeDeeptector: a deep-learning based method for detection of neural spiking activity.

Journal of neural engineering
OBJECTIVE: In electrophysiology, microelectrodes are the primary source for recording neural data (single unit activity). These microelectrodes can be implanted individually or in the form of arrays containing dozens to hundreds of channels. Recordin...

Biometric identification of listener identity from frequency following responses to speech.

Journal of neural engineering
OBJECTIVE: We investigate the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Chandrasekaran a...

Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks.

Artificial intelligence in medicine
Manual annotation is considered to be the "gold standard" in medical imaging analysis. However, medical imaging datasets that include expert manual segmentation are scarce as this step is time-consuming, and therefore expensive. Moreover, single-rate...

Robotic Systems in Operating Theaters: New Forms of Team-Machine Interaction in Health Care.

Methods of information in medicine
BACKGROUND: Health information systems have developed rapidly and considerably during the last decades, taking advantage of many new technologies. Robots used in operating theaters represent an exceptional example of this trend. Yet, the more these s...