AIMC Topic: Adolescent

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Accelerated Cine Cardiac MRI Using Deep Learning-Based Reconstruction: A Systematic Evaluation.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Breath-holding (BH) for cine balanced steady state free precession (bSSFP) imaging is challenging for patients with impaired BH capacity. Deep learning-based reconstruction (DLR) of undersampled k-space promises to shorten BHs while prese...

Health Care Trainees' and Professionals' Perceptions of ChatGPT in Improving Medical Knowledge Training: Rapid Survey Study.

Journal of medical Internet research
BACKGROUND: ChatGPT is a powerful pretrained large language model. It has both demonstrated potential and raised concerns related to knowledge translation and knowledge transfer. To apply and improve knowledge transfer in the real world, it is essent...

Comparison of Machine Learning Algorithms Using Manual/Automated Features on 12-Lead Signal Electrocardiogram Classification: A Large Cohort Study on Students Aged Between 6 to 18 Years Old.

Cardiovascular engineering and technology
PROPOSE: An electrocardiogram (ECG) has been extensively used to detect rhythm disturbances. We sought to determine the accuracy of different machine learning in distinguishing abnormal ECGs from normal ones in children who were examined using a rest...

Psychometric Properties of a Machine Learning-Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study.

Journal of medical Internet research
BACKGROUND: Medication adherence plays a critical role in controlling the evolution of chronic disease, as low medication adherence may lead to worse health outcomes, higher mortality, and morbidity. Assessment of their patients' medication adherence...

Convolutional Neural Network for Fully Automated Cerebellar Volumetry in Children in Comparison to Manual Segmentation and Developmental Trajectory of Cerebellar Volumes.

Cerebellum (London, England)
The purpose of this study was to develop a fully automated and reliable volumetry of the cerebellum of children during infancy and childhood using deep learning algorithms in comparison to manual segmentation. In addition, the clinical usefulness of ...

Electroencephalographic abnormalities in children with type 1 diabetes mellitus: a prospective study.

Turkish journal of medical sciences
BACKGROUND/AIM: The aim herein was to investigate epileptiform discharges on electroencephalogram (EEG), their correlation with glutamic acid decarboxylase 65 autoantibody (GAD-ab) in newly diagnosed pediatric type 1 diabetes mellitus (T1DM) patients...

Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence.

Translational psychiatry
Three-quarters of lifetime mental illness occurs by the age of 24, but relatively little is known about how to robustly identify youth at risk to target intervention efforts known to improve outcomes. Barriers to knowledge have included obtaining rob...

Pediatric Psoriasis Associated with Van Wyk Grumbach Syndrome: A case report.

La Tunisie medicale
INTRODUCTION: Psoriasis is a common chronic inflammatory condition, often beginning in childhood in approximately one-third of cases. It can be associated with various other autoimmune diseases such as rheumatoid arthritis, celiac disease, and thyroi...

Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Computers in biology and medicine
Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinical data from 390 children aged 4-17 years with asthma, with or without rhinitis, who received allergen immunotherapy (AIT). Combining these data, this ...