AIMC Topic: Adolescent

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Causal Discovery Analysis Reveals Insights into Psychosis Proneness, Brain Function, and Environmental Factors among Young Individuals.

Psychiatry research. Neuroimaging
Experiencing mild symptoms of psychosis, like delusions and hallucinations, occurs sometimes in general, nonclinical populations, often termed psychosis proneness (PP), potentially part of the psychosis continuum. Understanding the neural and environ...

Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.

Scientific reports
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...

Use of Artificial Intelligence in Adolescents' Mental Health Care: Systematic Scoping Review of Current Applications and Future Directions.

JMIR mental health
BACKGROUND: Given the increasing prevalence of mental health problems among adolescents, early intervention and appropriate management are needed to decrease mortality and morbidity. Artificial intelligence's (AI) potential contributions, although si...

Neuronal dynamics of slow and fast-motion motor imagery.

Neuroscience
Motor imagery (MI) is a cognitive process requiring mental simulation of physical actions, engaging neural networks that overlap with those activated during actual execution. This study investigated the neural correlates of slow and fast MI in ten he...

Comparison among artificial intelligence-based age estimation from morphological analysis of the pubic symphysis versus experienced and novice practitioners using a new atlas for component labeling.

International journal of legal medicine
Traditional age estimation methods based on macroscopic observation has been criticized for being excessively dependent on the observer's experience. The aim of this technical note is to propose a new atlas to assist the forensic practitioner in labe...

Explainable machine learning model predicting neurological deterioration in Wilson's disease via MRI radiomics and clinical features.

Parkinsonism & related disorders
BACKGROUND: This study aims to build a machine learning (ML) model to predict the deterioration of neurological symptoms in Wilson's disease (WD) patients during short-term anti-copper therapy. The model combines brain T1WI MRI radiomics with clinica...

Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.

Scientific reports
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of healthcare practitioners, transportation to health facilities, and other indirect costs. Furthermore, it...

The effects of learning experience on college students' deep english learning: a study of the chain mediation effect of motivation and strategy.

PloS one
This study focuses on the impact of learning experience on college students' deep learning of English and the chain-mediated effects of motivation and strategy. In the context of globalization, English is crucial for university students, but traditio...

Verification and application of deep learning models in daily sports activities of teenagers.

PloS one
With the development of smart wearable devices and deep learning (DL) technology, the monitoring and analysis of daily sports activities of teenagers face new opportunities. At present, traditional CNN (Convolutional Neural Network) models are mostly...