AIMC Topic: Affect

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The benefits of and barriers to using a social robot PARO in care settings: a scoping review.

BMC geriatrics
BACKGROUND: Given the complexity of providing dementia care in hospitals, integrating technology into practice is a high challenge and an important opportunity. Although there are a growing demand and interest in using social robots in a variety of c...

Artificial Intelligence based facial recognition for Mood Charting among men on life style modification and it's correlation with cortisol.

Asian journal of psychiatry
UNLABELLED: Today, clinicians and researchers believe that mood disorders in children and adolescents remain one of the most under diagnosed mental health problems. Mood disorders in adolescents also put them at risk for other conditions that may per...

Using automated computer vision and machine learning to code facial expressions of affect and arousal: Implications for emotion dysregulation research.

Development and psychopathology
As early as infancy, caregivers' facial expressions shape children's behaviors, help them regulate their emotions, and encourage or dissuade their interpersonal agency. In childhood and adolescence, proficiencies in producing and decoding facial expr...

Does integral affect influence intentions to use artificial intelligence for skin cancer screening? A test of the affect heuristic.

Psychology & health
This study investigated how influences people's processing of messages about risks and benefits of using autonomous artificial intelligence (AI) technology to screen for skin cancer. We examined (emotion derived during decision making) separately ...

Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.

PloS one
Facial expressions are fundamental to interpersonal communication, including social interaction, and allow people of different ages, cultures, and languages to quickly and reliably convey emotional information. Historically, facial expression researc...

Rapid detection of internalizing diagnosis in young children enabled by wearable sensors and machine learning.

PloS one
There is a critical need for fast, inexpensive, objective, and accurate screening tools for childhood psychopathology. Perhaps most compelling is in the case of internalizing disorders, like anxiety and depression, where unobservable symptoms cause c...

A signature-based machine learning model for distinguishing bipolar disorder and borderline personality disorder.

Translational psychiatry
Mobile technologies offer new opportunities for prospective, high resolution monitoring of long-term health conditions. The opportunities seem of particular promise in psychiatry where diagnoses often rely on retrospective and subjective recall of mo...

People are averse to machines making moral decisions.

Cognition
Do people want autonomous machines making moral decisions? Nine studies suggest that that the answer is 'no'-in part because machines lack a complete mind. Studies 1-6 find that people are averse to machines making morally-relevant driving, legal, me...

Self-Efficacy, Poststroke Depression, and Rehabilitation Outcomes: Is There a Correlation?

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The sudden live changes of stroke survivors may lead to negative psychological and behavioral outcomes, including anxiety and depressive mood, which may compromise the rehabilitation process. Some personality features, such as self-effica...

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

PloS one
Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy r...