AIMC Topic: Young Adult

Clear Filters Showing 11 to 20 of 4618 articles

Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions.

Scientific reports
Road traffic accidents (RTAs) in Northwest Ethiopia, a region with a fatality rate of 32.2 per 100,000 residents, pose a critical public health challenge exacerbated by infrastructural deficits and environmental hazards. This study leverages machine ...

Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex.

Scientific reports
The human thalamus projects nerve fibers to all cortical regions and propagates epileptic activity. However, opportunities to directly record thalamic and cortical neural activities simultaneously are extremely limited and their electrophysiological ...

Analyzing mental stress in Indian students through advanced machine learning and wearable technologies.

Scientific reports
Mental stress is a prevalent issue in modern society, and detecting and classifying it accurately is crucial for effective interventions and treatment plans. This study aims to compare various machine learning (ML) algorithms for detecting mental str...

EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation.

Scientific reports
Emotion recognition via EEG signals and facial analysis becomes one of the key aspects of human-computer interaction and affective computing, enabling scientists to gain insight into the behavior of humans. Classic emotion recognition methods usually...

Comparing ChatGPT and validated questionnaires in assessing loneliness and online social support among college students: a cross-sectional study.

Scientific reports
The capability of ChatGPT to understand and generate human-readable text has prompted the investigation of its potential as mental health assessment tools. This study aims to explore the validity of ChatGPT in assessing loneliness and online social s...

LLM-generated messages can persuade humans on policy issues.

Nature communications
The emergence of large language models (LLMs) has made it possible for generative artificial intelligence (AI) to tackle many higher-order cognitive tasks, with critical implications for industry, government, and labor markets. Here, we investigate w...

Enhanced role of the entorhinal cortex in adapting to increased working memory load.

Nature communications
In daily life, we frequently encounter varying demands on working memory (WM), yet how the brain adapts to high WM load remains unclear. To address this question, we recorded intracranial EEG from hippocampus, entorhinal cortex (EC), and lateral temp...

Prediction of axillary lymph node metastasis in triple negative breast cancer using MRI radiomics and clinical features.

Scientific reports
To develop and validate a machine learning-based prediction model to predict axillary lymph node (ALN) metastasis in triple negative breast cancer (TNBC) patients using magnetic resonance imaging (MRI) and clinical characteristics. This retrospective...

Identification of plasma proteins associated with seizures in epilepsy: A consensus machine learning approach.

PloS one
Blood-based biomarkers in epilepsy could constitute important research tools advancing neurobiological understanding and valuable clinical tools for better diagnosis and follow-up. An interesting question is whether biomarker patterns could contribut...

AI-augmented differential diagnosis of granulomatous rosacea and lupus miliaris disseminatus faciei: A 23-year retrospective pilot study.

PloS one
Granulomatous rosacea (GR) and lupus miliaris disseminatus faciei (LMDF) exhibit overlapping clinical features, making their differentiation challenging. While histopathological examination remains the gold standard, it is invasive and time-consuming...