AI Medical Compendium Topic:
Emotions

Clear Filters Showing 651 to 660 of 778 articles

Perception and sentiment analysis of palliative care in Chinese social media: Qualitative studies based on machine learning.

Social science & medicine (1982)
BACKGROUND: Traditional Chinese culture makes death a sensitive and taboo topic, leading patients and family members to refuse to choose palliative care.

Advancing emotion recognition with Virtual Reality: A multimodal approach using physiological signals and machine learning.

Computers in biology and medicine
INTRODUCTION: Emotion recognition systems have traditionally relied on basic visual elicitation. Virtual reality (VR) offers an immersive alternative that better resembles real-world emotional experiences.

Emotion recognition with multiple physiological parameters based on ensemble learning.

Scientific reports
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...

Constructing a predictive model of negative academic emotions in high school students based on machine learning methods.

Scientific reports
Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effectiveness of machine learning algorithms in predicting high school students' negative academic emotion...

Spatio-temporal CNN-BiLSTM dynamic approach to emotion recognition based on EEG signal.

Computers in biology and medicine
In this paper, a hybrid CNN-BiLSTM model for EEG-based emotion detection system is presented. The proposed technique is developed by extracting features using Power Spectral Density (PSD) signal. The proposed approach is carried out by combining CNN ...

Exploring customers' reuse intention to robots under different service failures: A mind perception perspective.

Acta psychologica
Artificial intelligence-based service robot failures (hereafter referred to as robot service failures) are inevitable in service practice, making the mitigation of their adverse effects a critical concern for service managers. The present paper inves...

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Behaviour research and therapy
Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and can further exacerbate existing mental health issues in those with depression. However, fewer studies have focused on the predictors of SA in adolescen...

EmT: A Novel Transformer for Generalized Cross-Subject EEG Emotion Recognition.

IEEE transactions on neural networks and learning systems
Integrating prior knowledge of neurophysiology into neural network architecture enhances the performance of emotion decoding. While numerous techniques emphasize learning spatial and short-term temporal patterns, there has been a limited emphasis on ...

Learning Emotion Category Representation to Detect Emotion Relations Across Languages.

IEEE transactions on pattern analysis and machine intelligence
Understanding human emotions is crucial for a myriad of applications, from psychological research to advancements in Natural Language Processing (NLP). Traditionally, emotions are categorized into distinct basic groups, which has led to the developme...

A novel deep learning model combining 3DCNN-CapsNet and hierarchical attention mechanism for EEG emotion recognition.

Neural networks : the official journal of the International Neural Network Society
Emotion recognition plays a key role in the field of human-computer interaction. Classifying and predicting human emotions using electroencephalogram (EEG) signals has consistently been a challenging research area. Recently, with the increasing appli...