AIMC Topic: Adolescent

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Applying machine learning to understand the role of social-emotional skills on subjective well-being and physical health.

Applied psychology. Health and well-being
Social-emotional skills are vital for individual development, yet research on which skills most effectively promote students' mental and physical health, particularly from a global perspective, remains limited. This study aims to address this gap by ...

Assessing COVID-19 Vaccine Effectiveness and Risk Factors for Severe Outcomes through Machine Learning Techniques: A Real-World Data Study in Andalusia, Spain.

Journal of epidemiology and global health
BACKGROUND: COVID-19 vaccination has become a pivotal global strategy in managing the pandemic. Despite COVID-19 no longer being classified as a Public Health Emergency of International Concern, the virus continues affecting people worldwide. This st...

Developmental changes in the perceived moral standing of robots.

Cognition
Emerging evidence suggests that children may think of robots-and artificial intelligence, more generally-as having moral standing. In this paper, we trace the developmental trajectory of this belief. Over three developmental studies (combined N = 415...

Height prediction of individuals with osteogenesis imperfecta by machine learning.

Orphanet journal of rare diseases
BACKGROUND: Osteogenesis imperfecta (OI) is a genetic disorder characterized by low bone mass, bone fragility and short stature. There is a significant gap in knowledge regarding the growth patterns across different types of OI, and the prediction of...

An explainable deep learning model to predict partial anomalous pulmonary venous connection for patients with atrial septal defect.

BMC pediatrics
BACKGROUND: Patients with partial anomalous pulmonary venous connection (PAPVC) usually present asymptomatic and accompanied by intricate anatomical types, which results in missed diagnosis from atrial septal defect (ASD). The present study aimed to ...

Improved patient identification by incorporating symptom severity in deep learning using neuroanatomic images in first episode schizophrenia.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Brain alterations associated with illness severity in schizophrenia remain poorly understood. Establishing linkages between imaging biomarkers and symptom expression may enhance mechanistic understanding of acute psychotic illness. Constructing model...

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

International journal of environmental research and public health
Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focused on predictors for current e-cigarette use among U.S. adults using feature selection and machine l...

Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.

BMC medical imaging
BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although contrast-enhanced computed tomography enterography is commonly used to evaluate crohn's disease, its imaging findings are often nonspecific and can ove...

Off-Body Sleep Analysis for Predicting Adverse Behavior in Individuals With Autism Spectrum Disorder.

IEEE journal of biomedical and health informatics
Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. Th...

Modeling Functional Brain Networks for ADHD via Spatial Preservation-Based Neural Architecture Search.

IEEE journal of biomedical and health informatics
Modeling functional brain networks (FBNs) for attention deficit hyperactivity disorder (ADHD) has sparked significant interest since the abnormal functional connectivity is discovered in certain functional magnetic resonance imaging (fMRI)-based brai...