AIMC Topic: Emotions

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Powerful tool or too powerful? Early public discourse about ChatGPT across 4 million tweets.

PloS one
BACKGROUND: This paper investigates initial exuberance and emotions surrounding ChatGPT's first three months of launch (1 December 2022-1 March 2023). The impetus for studying active discussions surrounding its implications, fears, and opinions is mo...

Propensity to trust shapes perceptions of comforting touch between trustworthy human and robot partners.

Scientific reports
Touching a friend to comfort or be comforted is a common prosocial behaviour, firmly based in mutual trust. Emphasising the interactive nature of trust and touch, we suggest that vulnerability, reciprocity and individual differences shape trust and p...

Leveraging the Sensitivity of Plants with Deep Learning to Recognize Human Emotions.

Sensors (Basel, Switzerland)
Recent advances in artificial intelligence combined with behavioral sciences have led to the development of cutting-edge tools for recognizing human emotions based on text, video, audio, and physiological data. However, these data sources are expensi...

Assessing the Impact of Urban Environments on Mental Health and Perception Using Deep Learning: A Review and Text Mining Analysis.

Journal of urban health : bulletin of the New York Academy of Medicine
Understanding how outdoor environments affect mental health outcomes is vital in today's fast-paced and urbanized society. Recently, advancements in data-gathering technologies and deep learning have facilitated the study of the relationship between ...

Who is behind the robot? The role of public social workers in implementing robotic eldercare program in South Korea.

Social work in health care
A companion robot named Hyodol is a digital technology implemented for eldercare in South Korea. Drawing insights from semi-structured interviews with public social workers actively involved in the Hyodol care program, this study explores how social ...

Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis.

Artificial intelligence in medicine
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with respect to the quantity of high-performing solutions reported in the literature. End users are particularly reluctant to rely on the opaque predictions of DL mo...

Hierarchical Context-Based Emotion Recognition With Scene Graphs.

IEEE transactions on neural networks and learning systems
For a better intention inference, we often try to figure out the emotional states of other people in social communications. Many studies on affective computing have been carried out to infer emotions through perceiving human states, i.e., facial expr...

Who should decide how limited healthcare resources are prioritized? Autonomous technology as a compelling alternative to humans.

PloS one
Who should decide how limited resources are prioritized? We ask this question in a healthcare context where patients must be prioritized according to their need and where advances in autonomous artificial intelligence-based technology offer a compell...

Decoding emotions: Exploring the validity of sentiment analysis in psychotherapy.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Process...

PASTFNet: a paralleled attention spatio-temporal fusion network for micro-expression recognition.

Medical & biological engineering & computing
Micro-expressions (MEs) play such an important role in predicting a person's genuine emotions, as to make micro-expression recognition such an important resea rch focus in recent years. Most recent researchers have made efforts to recognize MEs with ...