AI Medical Compendium Topic:
Emotions

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A scoping review of ontologies related to human behaviour change.

Nature human behaviour
Ontologies are classification systems specifying entities, definitions and inter-relationships for a given domain, with the potential to advance knowledge about human behaviour change. A scoping review was conducted to: (1) identify what ontologies e...

Group Differences in Facial Emotion Expression in Autism: Evidence for the Utility of Machine Classification.

Behavior therapy
Effective social communication relies, in part, on accurate nonverbal expression of emotion. To evaluate the nature of facial emotion expression (FEE) deficits in children with autism spectrum disorder (ASD), we compared 20 youths with ASD to a sampl...

Recognition of Emotions Using Multichannel EEG Data and DBN-GC-Based Ensemble Deep Learning Framework.

Computational intelligence and neuroscience
Fusing multichannel neurophysiological signals to recognize human emotion states becomes increasingly attractive. The conventional methods ignore the complementarity between time domain characteristics, frequency domain characteristics, and time-freq...

Sensor Information Fusion by Integrated AI to Control Public Emotion in a Cyber-Physical Environment.

Sensors (Basel, Switzerland)
The cyber-physical system (CPS) is a next-generation smart system that combines computing with physical space. It has been applied in various fields because the uncertainty of the physical world can be ideally controlled using cyber technology. In te...

Social robots to support children's well-being under medical treatment: A systematic state-of-the-art review.

Journal of child health care : for professionals working with children in the hospital and community
Hospitalization is a stressful experience for children. Socially assistive robots (SARs), designed to interact with humans, might be a means to mitigate a child's stress and support its well-being. A systematic state-of-the-art review was performed t...

Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging.

NeuroImage
An artificial neural network with multiple hidden layers (known as a deep neural network, or DNN) was employed as a predictive model (DNN) for the first time to predict emotional responses using whole-brain functional magnetic resonance imaging (fMRI...

Machine learning to support social media empowered patients in cancer care and cancer treatment decisions.

PloS one
BACKGROUND: A primary variant of social media, online support groups (OSG) extend beyond the standard definition to incorporate a dimension of advice, support and guidance for patients. OSG are complementary, yet significant adjunct to patient journe...

Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach.

Psychological medicine
BACKGROUND: The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition method...

The importance of recurrent top-down synaptic connections for the anticipation of dynamic emotions.

Neural networks : the official journal of the International Neural Network Society
Different studies have shown the efficiency of a feed-forward neural network in categorizing basic emotional facial expressions. However, recent findings in psychology and cognitive neuroscience suggest that visual recognition is not a pure bottom-up...