AIMC Topic: Adolescent
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Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.
PloS one
Apr 30, 2025
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.
Automated radiography assessment of ankle joint instability using deep learning.
Scientific reports
Apr 29, 2025
This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system...
Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study.
JMIR mHealth and uHealth
Apr 29, 2025
BACKGROUND: Considering the high prevalence of mental health conditions among young people and the technological advancements of artificial intelligence (AI)-based approaches in health services, mobile health (mHealth) apps for mental health are a pr...
Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 29, 2025
Exploring the pathogenic mechanisms of brain disorders within population is an important research in the field of neuroscience. Existing methods either combine clinical information to assist analysis or use data augmentation for sample expansion, ign...
Suicide risk prediction for Korean adolescents based on machine learning.
Scientific reports
Apr 28, 2025
Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, machine learning (ML) techniques have become progressively incorporated into psychiatric care. This stu...
Using machine learning approach to predict suicide ideation and suicide attempts among Chinese adolescents: A cross-sectional study.
Journal of affective disorders
Apr 25, 2025
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 ...
Machine learning for predicting medical outcomes associated with acute lithium poisoning.
Scientific reports
Apr 25, 2025
The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predicting medical outcomes. This study aimed to evaluate the effectiveness of the random forest algorithm ...
Modeling the number of new cases of childhood type 1 diabetes using Poisson regression and machine learning methods; a case study in Saudi Arabia.
PloS one
Apr 25, 2025
Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric populations. The escalating incidence of childhood type 1 diabetes (T1D) globally is a matter of increasing concern. Developing an effective model that l...
Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach.
Translational psychiatry
Apr 24, 2025
Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicide encompasses different phases, but for CSA survivors the salient factors precipitating suicide are rarely studied. In this study, from a progressive ...
Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.
BMC public health
Apr 23, 2025
INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its critical importance, comprehensive data on tobacco use among pregnant women in sub-Saharan Africa i...
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