AIMC Topic: Child

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Integrating machine learning and time-to-event models to explain and predict risk of hospitalization due to dengue in Colombia.

Scientific reports
Arboviral diseases such as dengue pose major public health challenges in endemic regions, notably in Norte de Santander (Colombia), where they place substantial pressure on healthcare services. We analyzed 8,814 confirmed dengue cases reported to the...

Predictive variables analysis for the tongue crib treatment of anterior crossbite in mixed dentition.

BMC oral health
OBJECTIVE: This study aimed to identify key prognostic variables and to develop and validate a clinical prediction model for pre-treatment assessment of tongue crib applicability.

Quantitative cytoarchitectural phenotyping of deparaffinized human brain tissues.

Communications biology
Advanced 3D imaging techniques and image segmentation and classification methods can transform biomedical research by offering insights into the human brain cytoarchitecture under pathological conditions. We propose a comprehensive pipeline for 3D im...

Longitudinal development of sex differences in the limbic system is associated with age, puberty and mental health.

Communications biology
Sex differences in mental health become more evident across adolescence, with a two-fold increase of prevalence of mood disorders in females compared to males. The brain underpinnings remain understudied. Here, we investigated the role of age, pubert...

An exploratory machine learning study on paediatric abdominal pain phenotyping and prediction.

PloS one
BACKGROUND: The exact mechanisms underlying paediatric abdominal pain (AP) remain unclear due to patient heterogeneity. This preliminary study aimed to identify AP phenotypes and develop predictive models to explore associated factors, with the goal ...

Deep learning-based automated detection of supernumerary teeth in pediatric panoramic radiographs.

PloS one
INTRODUCTION: Supernumerary teeth are a common developmental anomaly in pediatric patients, potentially leading to complications such as impaction, crowding, and delayed eruption. Accurate and early detection is critical to prevent these sequelae and...

Artificial intelligence-based method for detecting wrist fractures in children.

Scientific reports
Pediatric wrist fractures are common skeletal injuries in clinical practice; however, due to the ongoing development of children's bones, fracture characteristics are complex and often prone to misdiagnosis or missed diagnosis. Moreover, traditional ...

Quantitative Assessment of Strabismus Using Cloud AI Computing: Validation Study.

JMIR formative research
BACKGROUND: Strabismus measurement is essential in vision assessment and screening. It typically requires skilled clinicians or specialized equipment. Photographic strabismus measurement methods have value in terms of accessibility and convenience of...

Using a coloring activity to identify children's development of visual-motor integration: an application of artificial intelligence.

Annals of medicine
AIM: Visual-motor integration (VMI) is an important indicator in children with learning disabilities. We aimed to use performance in a coloring activity to identify children's VMI developmental status.

Skel-Net: automatic prediction of skeletal pattern on scanned lateral cephalograms using anatomical prior-guided deep learning network.

BMC oral health
BACKGROUND: Estimating craniofacial patterns is essential for successful orthodontic treatment. However, conventional static measurements are inadequate for capturing dynamic changes, and manual cephalometric analysis is labor-intensive and requires ...