AIMC Topic: Adolescent

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Algorithmic and sensor-based research on Chinese children's and adolescents' screen use behavior and light environment.

Frontiers in public health
BACKGROUND: Myopia poses a global health concern and is influenced by both genetic and environmental factors. The incidence of myopia tends to increase during infectious outbreaks, such as the COVID-19 pandemic. This study examined the screen-time be...

Both Patients and Plastic Surgeons Prefer Artificial Intelligence-Generated Microsurgical Information.

Journal of reconstructive microsurgery
BACKGROUND:  With the growing relevance of artificial intelligence (AI)-based patient-facing information, microsurgical-specific online information provided by professional organizations was compared with that of ChatGPT (Chat Generative Pre-Trained ...

Age and sex estimation in cephalometric radiographs based on multitask convolutional neural networks.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: Age and sex characteristics are evident in cephalometric radiographs (CRs), yet their accurate estimation remains challenging due to the complexity of these images. This study aimed to harness deep learning to automate age and sex estimat...

Prediction of suicidal ideation among preadolescent children with machine learning models: A longitudinal study.

Journal of affective disorders
BACKGROUND: Machine learning (ML) has been widely used to predict suicidal ideation (SI) in adolescents and adults. Nevertheless, studies of accurate and efficient models of SI prediction with preadolescent children are still needed because SI is sur...

Robot-Assisted Ureteroplasty with Labial Mucosal Onlay Grafting for Long Left-Sided Proximal Ureteral Stenosis in Children and Adolescents: Technical Tips and Functional Outcomes.

Journal of endourology
To evaluate functional outcomes of robot-assisted ureteroplasty with labial mucosa grafting for long proximal ureteral stenosis (LPUS) in children and adolescents. Included in this study were 15 patients who underwent robot-assisted ureteroplasty w...

Accelerating computer vision-based human identification through the integration of deep learning-based age estimation from 2 to 89 years.

Scientific reports
Computer Vision (CV)-based human identification using orthopantomograms (OPGs) has the potential to identify unknown deceased individuals by comparing postmortem OPGs with a comprehensive antemortem CV database. However, the growing size of the CV da...

Deep learning segmentation of organs-at-risk with integration into clinical workflow for pediatric brain radiotherapy.

Journal of applied clinical medical physics
PURPOSE: Radiation therapy (RT) of pediatric brain cancer is known to be associated with long-term neurocognitive deficits. Although target and organs-at-risk (OARs) are contoured as part of treatment planning, other structures linked to cognitive fu...

Timing matters for accurate identification of the epileptogenic zone.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Interictal biomarkers of the epileptogenic zone (EZ) and their use in machine learning models open promising avenues for improvement of epilepsy surgery evaluation. Currently, most studies restrict their analysis to short segments of intra...

Deep learning algorithm for automatically measuring Cobb angle in patients with idiopathic scoliosis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: The Cobb angle is a standard measurement to qualify and track the progression of scoliosis. However, the Cobb angle has high inter- and intra-observer variability. Consequently, its measurement varies with vertebrae and may even differ when ...

Automated Detection of Pediatric Foreign Body Aspiration from Chest X-rays Using Machine Learning.

The Laryngoscope
OBJECTIVE/HYPOTHESIS: Standard chest radiographs are a poor diagnostic tool for pediatric foreign body aspiration. Machine learning may improve upon the diagnostic capabilities of chest radiographs. The objective is to develop a machine learning algo...