AIMC Topic: Adolescent

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Game Design, Effectiveness, and Implementation of Serious Games Promoting Aspects of Mental Health Literacy Among Children and Adolescents: Systematic Review.

JMIR mental health
BACKGROUND: The effects of traditional health-promoting and preventive interventions in mental health and mental health literacy are often attenuated by low adherence and user engagement. Gamified approaches such as serious games (SGs) may be useful ...

Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model.

BMC medical imaging
OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tuberculum sellar meningiomas (TSMs) are common sellar region lesions with similar imaging characteristics, making differential diagnosis challenging. Thi...

Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke.

BMC neurology
BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated ...

Prediction of High-Dose Methotrexate Blood Concentration in Osteosarcoma Patients Using Machine Learning.

Drug design, development and therapy
INTRODUCTION: High-dose methotrexate is a typical chemotherapy that is widely used in the treatment of osteosarcoma. However, the unique dose-response relationship of methotrexate makes its treatment window relatively narrow, and its clinical use is ...

Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging data sets for research. Consequently, pediatric neuroscience research lags adult counterparts,...

Machine Learning for Predicting Critical Events Among Hospitalized Children.

JAMA network open
IMPORTANCE: Unrecognized deterioration among hospitalized children is associated with a high risk of mortality and morbidity. The current approach to pediatric risk stratification is fragmented, as each hospital unit (emergency, ward, or intensive ca...

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BMC medical imaging
BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for adrenal CT measurements in clinical practice. This study aims to develop a deep learning (DL) model for automated adrenal gland segmentation on non-con...

Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care.

BMC medicine
BACKGROUND: The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis.

Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.

Journal of neurodevelopmental disorders
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...

Predicting the onset of mental health problems in adolescents.

Psychological medicine
OBJECTIVE: Mental health problems are the major cause of disability among adolescents. Personalized prevention may help to mitigate the development of mental health problems, but no tools are available to identify individuals at risk before they requ...