AIMC Topic: Adolescent
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Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.
Frontiers in public health
May 29, 2025
BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12. 8 to 45 per 100,000 and incidence rates from 7.8 to 8.3 per 100,000 person-years. The diagnosis of...
Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longitudinal study.
Journal of affective disorders
May 28, 2025
BACKGROUND: Major depressive disorder (MDD) is characterized by significant heterogeneity in treatment response, with inflammation hypothesized to play a role in its pathophysiology. Peripheral inflammatory biomarkers, such as the neutrophil-to-lymph...
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
May 28, 2025
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...
Functional connectome-based predictive modeling of suicidal ideation.
Journal of affective disorders
May 27, 2025
Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to ident...
Leveraging pre-vaccination antibody titres across multiple influenza H3N2 variants to forecast the post-vaccination response.
EBioMedicine
May 26, 2025
BACKGROUND: Despite decades of research on the influenza virus, we still lack a predictive understanding of how vaccination reshapes each person's antibody response, which impedes efforts to design better vaccines. Models using pre-vaccination antibo...
Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features.
BMC psychiatry
May 26, 2025
BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abno...
A pediatric ECG database with disease diagnosis covering 11643 children.
Scientific data
May 26, 2025
Electrocardiogram (ECG) is a common non-invasive diagnostic tool for cardiovascular diseases. Adequate data is crucial in utilizing deep learning to achieve intelligent diagnosis of ECG. The existing ECG datasets almost only focus on adults and most ...
Ambivalent User Needs as a Challenge and Chance for the Design of a Web-Based Intervention for Gaming Disorder: Qualitative Interview Study With Adolescents and Young Adults.
JMIR formative research
May 26, 2025
BACKGROUND: In Germany, there are still many young people with gaming disorder (GD) who do not use or cannot access existing treatment services. Given the increasing prevalence of internet use disorders and GD, especially among young people in German...
Automated landmark-based mid-sagittal plane: reliability for 3-dimensional mandibular asymmetry assessment on head CT scans.
Clinical oral investigations
May 26, 2025
OBJECTIVE: The determination of the mid-sagittal plane (MSP) on three-dimensional (3D) head imaging is key to the assessment of facial asymmetry. The aim of this study was to evaluate the reliability of an automated landmark-based MSP to quantify man...
IoT-enabled real-time health monitoring system for adolescent physical rehabilitation.
Scientific reports
May 23, 2025
This study aims to develop an intelligent system leveraging Internet of Thing (IoT) technology to enhance the precision of youth physical training monitoring and improve training outcomes. A wearable device incorporating Micro Electro Mechanical Syst...
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