AIMC Topic:
Young Adult

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Insights from EEG analysis of evoked memory recalls using deep learning for emotion charting.

Scientific reports
Affect recognition in a real-world, less constrained environment is the principal prerequisite of the industrial-level usefulness of this technology. Monitoring the psychological profile using smart, wearable electroencephalogram (EEG) sensors during...

Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.

Environmental monitoring and assessment
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory dise...

Machine learning for automating subjective clinical assessment of gait impairment in people with acquired brain injury - a comparison of an image extraction and classification system to expert scoring.

Journal of neuroengineering and rehabilitation
BACKGROUND: Walking impairment is a common disability post acquired brain injury (ABI), with visually evident arm movement abnormality identified as negatively impacting a multitude of psychological factors. The International Classification of Functi...

Deep Learning-Enabled Vasculometry Depicts Phased Lesion Patterns in High Myopia Progression.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To investigate the potential phases in myopic retinal vascular alterations for further elucidating the mechanisms underlying the progression of high myopia (HM).

Brain age prediction using interpretable multi-feature-based convolutional neural network in mild traumatic brain injury.

NeuroImage
BACKGROUND: Convolutional neural network (CNN) can capture the structural features changes of brain aging based on MRI, thus predict brain age in healthy individuals accurately. However, most studies use single feature to predict brain age in healthy...

Anxiety in young people: Analysis from a machine learning model.

Acta psychologica
The study addresses the detection of anxiety symptoms in young people using artificial intelligence models. Questionnaires such as the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder 7-item scale (GAD-7) are used to collect da...

Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG.

Medical & biological engineering & computing
Stroke is a neurological condition that usually results in the loss of voluntary control of body movements, making it difficult for individuals to perform activities of daily living (ADLs). Brain-computer interfaces (BCIs) integrated into robotic sys...

Validation of a novel, low-fidelity virtual reality simulator and an artificial intelligence assessment approach for peg transfer laparoscopic training.

Scientific reports
Simulators are widely used in medical education, but objective and automatic assessment is not feasible with low-fidelity simulators, which can be solved with artificial intelligence (AI) and virtual reality (VR) solutions. The effectiveness of a cus...

Preparatory activity of anterior insula predicts conflict errors: integrating convolutional neural networks and neural mass models.

Scientific reports
Preparatory brain activity is a cornerstone of proactive cognitive control, a top-down process optimizing attention, perception, and inhibition, fostering cognitive flexibility and adaptive attention control in the human brain. In this study, we prop...