AI Medical Compendium Topic:
Child

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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...

The marital and fertility sentiment orientation of Chinese women and its influencing factors - An analysis based on natural language processing.

PloS one
BACKGROUND: With the evolution of China's social structure and values, there has been a shift in attitudes towards marriage and fertility, with an increasing number of women holding diverse perspectives on these matters. In order to better comprehend...

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...

A fully automatic deep learning-based method for segmenting regions of interest and predicting renal function in pediatric dynamic renal scintigraphy.

Annals of nuclear medicine
OBJECTIVE: Accurate delineation of renal regions of interest (ROIs) is critical for the assessment of renal function in pediatric dynamic renal scintigraphy (DRS). The purpose of this study was to develop and evaluate a deep learning (DL) model that ...

[Robot-assisted kidney transplantation-what is new?].

Urologie (Heidelberg, Germany)
BACKGROUND: The first robot-assisted kidney transplantation (RAKT) was conducted in 2010, and the first time in Germany in 2016. As more than 5 years have passed, current evidence, technological developments and the latest (German) experience are pre...

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...

Pediatric diabetes prediction using deep learning.

Scientific reports
This study proposed a novel technique for early diabetes prediction with high accuracy. Recently, Deep Learning (DL) has been proven to be expeditious in the diagnosis of diabetes. The supported model is constructed by implementing ten hidden layers ...

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development.

Environmental research
BACKGROUND: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome st...