AIMC Topic: Young Adult

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Chinese EFL students' perceptions about the role of artificial intelligence (AI) technologies in their second language (L2) self-concept.

Acta psychologica
The applications of Artificial Intelligence (AI) technologies to second or foreign language (L2) education have recently been the focus of several studies in the literature. However, the impact of AI tools on students' psychological-affective states ...

Significance of Papillary and Trabecular Muscular Volume in Right Ventricular Volumetry with Cardiac MR Imaging.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: Pulmonary valve regurgitation after repaired Tetralogy of Fallot (TOF) or double-outlet right ventricle (DORV) causes hypertrophy and papillary muscle enlargement. Cardiac magnetic resonance imaging (CMR) can evaluate the right ventricular (...

Selection of representative electrodes for stereoscopic visual comfort studies in conjunction with brain mechanism analysis.

Brain research
The widespread use of 3D stereoscopic technology has drawn attention to the problem of visual discomfort, several studies have used EEG to assess visual comfort and discomfort phenomena, but there is a lack of scientific basis for the selection of el...

Interpretable Machine Learning approach for predicting clinically significant suicide risk: A case study of patients with major depressive disorder in Greece.

Psychiatry research
Suicide prevention is currently a global public health priority, since suicide has been a prevalent cause of death or potential loss of life. Multiple factors contribute to suicide risk, such as depression and a history of attempted suicide among oth...

Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections.

European radiology experimental
BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (RPE), which is a prognostic imaging biomarker for a severe course of illness. This study aimed to develop a deep learning-based algorithm for the auto...

Gene expression profiles associated with gray matter and dynamic connectivity disruptions in major depressive disorder.

Journal of affective disorders
PURPOSE: To identify biomarkers linking molecular mechanisms to macroscale brain changes in major depressive disorder (MDD) by integrating multimodal neuroimaging, transcriptomics, and machine learning.

Development and validation of a machine learning model to predict cognitive behavioral therapy outcome in obsessive-compulsive disorder using clinical and neuroimaging data.

Journal of affective disorders
BACKGROUND: Cognitive behavioral therapy (CBT) is a first-line treatment for obsessive-compulsive disorder (OCD), but clinical response is difficult to predict. In this study, we aimed to develop predictive models using clinical and neuroimaging data...

Effects of robot arm design and movement speed during human-robot interaction.

Applied ergonomics
The purpose of this experiment was to investigate the effect of robot arm size, movement speed, and degrees of freedom on perceived safety, trust, mental workload, human behaviors, and task performance in a collaborative pick-and-place task. Fifty-si...

Machine learning to predict mitochondrial diseases by phenotypes.

Mitochondrion
Diagnosing mitochondrial diseases remains challenging because of the heterogeneous symptoms. This study aims to use machine learning to predict mitochondrial diseases from phenotypes to reduce genetic testing costs. This study included patients who u...

Shared and distinct neural signatures of feature and spatial attention.

NeuroImage
The debate on whether feature attention (FA) and spatial attention (SA) share a common neural mechanism remains unresolved. Previous neuroimaging studies have identified fronto-parietal-temporal attention-related regions that exhibited consistent act...