AIMC Topic: Child

Clear Filters Showing 2841 to 2850 of 3433 articles

Urinary Metabolic Biomarkers of Attentional Control in Children With Attention-Deficit/Hyperactivity Disorder: A Dimensional Approach Through H NMR-Based Metabolomics.

NMR in biomedicine
Enhancing the understanding of attention-deficit/hyperactivity disorder (ADHD) by linking biological processes with behavioral manifestations is a primary objective of the Research Domain Criteria (RDoC) framework, which aims to transcend traditional...

[Artificial intelligence in preventive medicine for children and adolescents-applications and acceptance].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
The use of artificial intelligence (AI) in pediatric and adolescent medicine offers numerous possibilities, particularly in the prevention of chronic diseases. AI-powered applications such as machine learning for the analysis of speech or movement pa...

Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.

Computers in biology and medicine
Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, leads to significant alterations in brain structure. This study used machine learning (ML) to estimate brain age from structural MRI scans and investigate...

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

Nature reviews. Nephrology
The kidney is a target organ for the dysregulated host response to infection that defines sepsis, and acute kidney injury (AKI) is often an early manifestation of this response. Current sepsis criteria for adults (Sepsis-3) continue to include outmod...

Applying exposure-response analysis to enhance Mycophenolate Mofetil dosing precision in pediatric patients with immune-mediated renal diseases by machine learning models.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
BACKGROUND: Mycophenolate mofetil (MMF), a cornerstone immunosuppressant for lupus nephritis, is increasingly used off-label in pediatric immune-mediated renal diseases. The aims of this study were to develop and validate pharmacokinetic models for m...

Machine learning-based approaches for distinguishing viral and bacterial pneumonia in paediatrics: A scoping review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource settings. Accurate differentiation between viral and bacterial pneumonia is essential for guiding approp...

Using machine learning approach to predict suicide ideation and suicide attempts among Chinese adolescents: A cross-sectional study.

Journal of affective disorders
BACKGROUND: Screening for suicide ideation and suicide attempts is crucial for adolescents, yet accurately predicting these outcomes remains a significant challenge. The relationship between non-suicidal self-injury and suicide ideation and attempts ...

The effect of social robot interventions on anxiety in children in clinical settings: a systematic review and meta-analysis.

Journal of affective disorders
AIMS: Children in clinical settings are prone to anxiety due to developmental limitations, which hinders treatment progress. This systematic review and meta-analysis aimed to evaluate the efficacy of social robot interventions compared to routine car...

Prediction of first attempt of suicide in early adolescence using machine learning.

Journal of affective disorders
BACKGROUND: Suicide is the second leading cause of death among early adolescents, yet the first onset of suicide attempts during this critical developmental period remains poorly understood. This study aimed to identify key characteristics associated...