AIMC Topic: Emotions

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Innovative machine learning approach and evaluation campaign for predicting the subjective feeling of work-life balance among employees.

PloS one
At present, many researchers see hope that artificial intelligence, machine learning in particular, will improve several aspects of the everyday life for individuals, cities and whole nations alike. For example, it has been speculated that the so-cal...

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

NeuroImage. Clinical
Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of ...

Using artificial intelligence to examine online patient reviews.

Journal of health psychology
Healthcare consumers are increasingly turning to online sources such as educational websites, forums and social media platforms to share their experiences with medical services and to demystify the uncertainties associated with undergoing various pro...

Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion.

Sensors (Basel, Switzerland)
The paper proposes a method of visual attention-based emotion classification through eye gaze analysis. Concretely, tensor-based emotional category classification via visual attention-based heterogeneous convolutional neural network (CNN) feature fus...

Achieving affective human-virtual agent communication by enabling virtual agents to imitate positive expressions.

Scientific reports
Affective communication, communicating with emotion, during face-to-face communication is critical for social interaction. Advances in artificial intelligence have made it essential to develop affective human-virtual agent communication. A person's b...

Deep Joint Spatiotemporal Network (DJSTN) for Efficient Facial Expression Recognition.

Sensors (Basel, Switzerland)
Understanding a person's feelings is a very important process for the affective computing. People express their emotions in various ways. Among them, facial expression is the most effective way to present human emotional status. We propose efficient ...

Academic Emotion Classification and Recognition Method for Large-scale Online Learning Environment-Based on A-CNN and LSTM-ATT Deep Learning Pipeline Method.

International journal of environmental research and public health
Subjective well-being is a comprehensive psychological indicator for measuring quality of life. Studies have found that emotional measurement methods and measurement accuracy are important for well-being-related research. Academic emotion is an emoti...

Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning.

Brain connectivity
Hierarchical organization of brain function has been an established concept in the neuroscience field for a long time, however, it has been rarely demonstrated how such hierarchical macroscale functional networks are actually organized in the human b...

Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories.

PloS one
BACKGROUND: Online Cancer Support Groups (OCSG) are becoming an increasingly vital source of information, experiences and empowerment for patients with cancer. Despite significant contributions to physical, psychological and emotional wellbeing of pa...

The Design of CNN Architectures for Optimal Six Basic Emotion Classification Using Multiple Physiological Signals.

Sensors (Basel, Switzerland)
This study aimed to design an optimal emotion recognition method using multiple physiological signal parameters acquired by bio-signal sensors for improving the accuracy of classifying individual emotional responses. Multiple physiological signals su...