AI Medical Compendium Topic

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Recognition, Psychology

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Improving the diagnostic value of lineup rejections.

Cognition
Erroneous eyewitness identification evidence is likely the leading cause of wrongful convictions. To minimize this error, scientists recommend collecting confidence. Research shows that eyewitness confidence and accuracy are strongly related when an ...

Automated analysis of a novel object recognition test in mice using image processing and machine learning.

Behavioural brain research
The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' obs...

Human Visual Pathways for Action Recognition versus Deep Convolutional Neural Networks: Representation Correspondence in Late but Not Early Layers.

Journal of cognitive neuroscience
Deep convolutional neural networks (DCNNs) have attained human-level performance for object categorization and exhibited representation alignment between network layers and brain regions. Does such representation alignment naturally extend to other v...

A temporal-spatial feature fusion network for emotion recognition with individual differences reduction.

Neuroscience
PURPOSE: In the context of EEG-based emotion recognition tasks, a conventional strategy involves the extraction of spatial and temporal features, subsequently fused for emotion prediction. However, due to the pronounced individual variability in EEG ...

An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.

Journal of neuroscience methods
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...

Benchmarking the speed-accuracy tradeoff in object recognition by humans and neural networks.

Journal of vision
Active object recognition, fundamental to tasks like reading and driving, relies on the ability to make time-sensitive decisions. People exhibit a flexible tradeoff between speed and accuracy, a crucial human skill. However, current computational mod...

Model-agnostic meta-learning for EEG-based inter-subject emotion recognition.

Journal of neural engineering
. Developing an efficient and generalizable method for inter-subject emotion recognition from neural signals is an emerging and challenging problem in affective computing. In particular, human subjects usually have heterogeneous neural signal charact...

Combining Real-Time Neuroimaging With Machine Learning to Study Attention to Familiar Faces During Infancy: A Proof of Principle Study.

Developmental science
Looking at caregivers' faces is important for early social development, and there is a concomitant increase in neural correlates of attention to familiar versus novel faces in the first 6 months. However, by 12 months of age brain responses may not d...

Can AI-generated faces serve as fillers in eyewitness lineups?

Memory (Hove, England)
To create a photo lineup for an eyewitness, police embed the suspect in a group of similar-looking individuals (i.e., fillers). If the witness selects the suspect from these photos of similar-looking people, then this provides evidence they remember ...

AI assistance improves people's ability to distinguish correct from incorrect eyewitness lineup identifications.

Proceedings of the National Academy of Sciences of the United States of America
Mistaken eyewitness identification is one of the leading causes of false convictions. Improving law enforcement's ability to identify correct identifications could have profound implications for criminal justice. Across two experiments, we show that ...