AIMC Topic: Young Adult

Clear Filters Showing 501 to 510 of 4802 articles

Humans take the visuospatial perspective of robots and objects that imply social presence.

Acta psychologica
Visual perspective-taking (VPT) plays a crucial role in social interactions. Although the mechanisms behind VPT have been thoroughly studied in human-human interactions, there are only a few studies examining whether humans can also adopt the visuosp...

AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
BACKGROUND: AI-aided home stethoscopes offer the opportunity of continuous remote monitoring of cystic fibrosis (CF) patients, reducing the need for clinic visits.

Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward.

BMC medical education
BACKGROUND: Measuring artificial intelligence (AI) readiness among medical students is essential to assess how prepared future doctors are to work with AI technology. Therefore, this study aimed to examine the factors influencing AI readiness among m...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

Scientific reports
This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18-85) in Southeastern Virginia (2016-2020), we found Mood Affective Disorders we...

Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

European radiology experimental
BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic resonance angiography (MRA) (relaxation-enhanced angiography without contrast and triggering, REACT) of neck arteries using compressed SENSE (CS) com...

Supervised machine learning compared to large language models for identifying functional seizures from medical records.

Epilepsia
OBJECTIVE: The Functional Seizures Likelihood Score (FSLS) is a supervised machine learning-based diagnostic score that was developed to differentiate functional seizures (FS) from epileptic seizures (ES). In contrast to this targeted approach, large...

Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification.

Sensors (Basel, Switzerland)
This study explores the link between the emotion "guilt" and human EEG data, and investigates the influence of gender differences on the expression of guilt and neutral emotions in response to visual stimuli. Additionally, the stimuli used in the stu...

Prediction of depressive disorder using machine learning approaches: findings from the NHANES.

BMC medical informatics and decision making
BACKGROUND: Depressive disorder, particularly major depressive disorder (MDD), significantly impact individuals and society. Traditional analysis methods often suffer from subjectivity and may not capture complex, non-linear relationships between ris...

Prediction of tuberculosis treatment outcomes using biochemical makers with machine learning.

BMC infectious diseases
BACKGROUND: Tuberculosis (TB) continues to pose a significant threat to global public health. Enhancing patient prognosis is essential for alleviating the disease burden.