AI Medical Compendium Topic:
Child

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Enhancement of Non-Linear Deep Learning Model by Adjusting Confounding Variables for Bone Age Estimation in Pediatric Hand X-rays.

Journal of digital imaging
In medicine, confounding variables in a generalized linear model are often adjusted; however, these variables have not yet been exploited in a non-linear deep learning model. Sex plays important role in bone age estimation, and non-linear deep learni...

Design Path for a Social Robot for Emotional Communication for Children with Autism Spectrum Disorder (ASD).

Sensors (Basel, Switzerland)
Children with autism spectrum disorder (ASD) have deficits in social interaction and expressing and understanding emotions. Based on this, robots for children with ASD have been proposed. However, few studies have been conducted about how to design a...

Barriers and facilitators to physical activity and further digital exercise intervention among inactive British adolescents in secondary schools: a qualitative study with physical education teachers.

Frontiers in public health
BACKGROUND: Previous studies indicated that physical education programs in schools were unsuccessful to ameliorate physical activity (PA) behaviors among adolescents. This study investigated PE teachers' perceptions of barriers and facilitators to PA...

Predicting congenital syphilis cases: A performance evaluation of different machine learning models.

PloS one
BACKGROUND: Communicable diseases represent a huge economic burden for healthcare systems and for society. Sexually transmitted infections (STIs) are a concerning issue, especially in developing and underdeveloped countries, in which environmental fa...

Robotic approach to the uretero-vesical junction in children: An international multicentric retrospective study.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Robot-assisted approach to UVJ is getting more and more used in pediatric patients.

Development of a Deep Learning Model for Retinal Hemorrhage Detection on Head Computed Tomography in Young Children.

JAMA network open
IMPORTANCE: Abusive head trauma (AHT) in children is often missed in medical encounters, and retinal hemorrhage (RH) is considered strong evidence for AHT. Although head computed tomography (CT) is obtained routinely, all but exceptionally large RHs ...

Handwriting Evaluation Using Deep Learning with SensoGrip.

Sensors (Basel, Switzerland)
Handwriting learning disabilities, such as dysgraphia, have a serious negative impact on children's academic results, daily life and overall well-being. Early detection of dysgraphia facilitates an early start of targeted intervention. Several studie...

A Review Paper about Deep Learning for Medical Image Analysis.

Computational and mathematical methods in medicine
Medical imaging refers to the process of obtaining images of internal organs for therapeutic purposes such as discovering or studying diseases. The primary objective of medical image analysis is to improve the efficacy of clinical research and treatm...

Multiview child motor development dataset for AI-driven assessment of child development.

GigaScience
BACKGROUND: Children's motor development is a crucial tool for assessing developmental levels, identifying developmental disorders early, and taking appropriate action. Although the Korean Developmental Screening Test for Infants and Children (K-DST)...

Prediction of MYCN Gene Amplification in Pediatric Neuroblastomas: Development of a Deep Learning-Based Tool for Automatic Tumor Segmentation and Comparative Analysis of Computed Tomography-Based Radiomics Features Harmonization.

Journal of computer assisted tomography
OBJECTIVE: MYCN oncogene amplification is closely linked to high-grade neuroblastoma with poor prognosis. Accurate quantification is essential for risk assessment, which guides clinical decision making and disease management. This study proposes an e...