AI Medical Compendium Topic

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Models, Psychological

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Modeling learner-controlled mental model learning processes by a second-order adaptive network model.

PloS one
Learning knowledge or skills usually is considered to be based on the formation of an adequate internal mental model as a specific type of mental network. The learning process for such a mental model conceptualised as a mental network, is a form of (...

COVID-19 sentiment analysis via deep learning during the rise of novel cases.

PloS one
Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic ev...

Behavioral correlates of cortical semantic representations modeled by word vectors.

PLoS computational biology
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field o...

Using large-scale experiments and machine learning to discover theories of human decision-making.

Science (New York, N.Y.)
Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this go...

Explaining distortions in metacognition with an attractor network model of decision uncertainty.

PLoS computational biology
Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that mo...

EEG-based detection of emotional valence towards a reproducible measurement of emotions.

Scientific reports
A methodological contribution to a reproducible Measurement of Emotions for an EEG-based system is proposed. Emotional Valence detection is the suggested use case. Valence detection occurs along the interval scale theorized by the Circumplex Model of...

A mental models approach for defining explainable artificial intelligence.

BMC medical informatics and decision making
BACKGROUND: Wide-ranging concerns exist regarding the use of black-box modelling methods in sensitive contexts such as healthcare. Despite performance gains and hype, uptake of artificial intelligence (AI) is hindered by these concerns. Explainable A...

Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning.

Scientific reports
Autism spectrum disorder (ASD) is the fourth most common neurodevelopmental disorder, with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such individuals are scarce. This has led to increasing interest in the developmen...

Unpredictable robots elicit responsibility attributions.

The Behavioral and brain sciences
Do people hold robots responsible for their actions? While Clark and Fischer present a useful framework for interpreting social robots, we argue that they fail to account for people's willingness to assign responsibility to robots in certain contexts...

Three Challenges for AI-Assisted Decision-Making.

Perspectives on psychological science : a journal of the Association for Psychological Science
Artificial intelligence (AI) has the potential to improve human decision-making by providing decision recommendations and problem-relevant information to assist human decision-makers. However, the full realization of the potential of human-AI collabo...