AIMC Topic: Adolescent

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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...

Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model.

Frontiers in public health
INTRODUCTION: This study investigates the potential of a deep learning-based Life Log Sharing Model (LLSM) to enhance adolescent physical fitness and exercise behaviors through personalized public health interventions.

Prediction of remission of pharmacologically treated psychotic depression: A machine learning approach.

Journal of affective disorders
BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment for major depressive disorder with psychotic features ('psychotic depression'). The present study aims to identify sociodemographic and clinical pred...

Refining early detection of Marburg Virus Disease (MVD) in Rwanda: Leveraging predictive symptom clusters to enhance case definitions.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
BACKGROUND: Marburg Virus Disease (MVD) poses a significant global health risk due to its high case fatality rates (24%-88%) and the diagnostic challenges posed by its nonspecific early symptoms, which overlap with other febrile illnesses like malari...

Can artificial ıntelligence detect the anti-aging effect of rhinoplasty?

Journal of plastic surgery and hand surgery
BACKGROUND: The quest for eternal youth has been a common theme in many cultures for centuries. While we have yet to discover a way to preserve youth eternally, we have made significant progress in understanding the aging process and in developing ph...

Contemporary digital marketing techniques used in unhealthy food campaigns targeting young people.

Appetite
The digital marketing of unhealthy foods and non-alcoholic beverages has a detrimental impact on children's eating behaviours, leading to adverse diet-related health outcomes. To inform the development of evidence-based strategies to protect children...

Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.

Scientific reports
Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-threatening in critically ill children, and the quest for an accurate and efficient method for early DIC prediction is of paramount importance. Candidate ...

Trade-off of different deep learning-based auto-segmentation approaches for treatment planning of pediatric craniospinal irradiation autocontouring of OARs for pediatric CSI.

Medical physics
BACKGROUND: As auto-segmentation tools become integral to radiotherapy, more commercial products emerge. However, they may not always suit our needs. One notable example is the use of adult-trained commercial software for the contouring of organs at ...

Development and validation of a machine learning model for predicting pediatric metabolic syndrome using anthropometric and bioelectrical impedance parameters.

International journal of obesity (2005)
OBJECTIVE: Metabolic syndrome (MS) is a risk factor for cardiovascular diseases, and its prevalence is increasing among children and adolescents. This study developed a machine learning model to predict MS using anthropometric and bioelectrical imped...

Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.

NeuroImage
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...