AIMC Topic: Adolescent

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Understanding the role of hormones in pediatric growth: Insights from a double-debiased machine learning approach.

Steroids
This study investigates the causal relationships between hormone levels and growth and development of children, focusing specifically on height disparities in cases of dwarfism. Besides utilizing double-debiased machine learning approach, the study i...

Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?

Journal of neurosurgery. Pediatrics
OBJECTIVE: The Endoscopic Third Ventriculostomy Success Score (ETVSS) is a useful decision-making heuristic when considering the probability of surgical success, defined traditionally as no repeat cerebrospinal fluid diversion surgery needed within 6...

AcidAGE: a biological age determination neural network based on urine organic acids.

Biogerontology
Organic acids reflect the course of all important metabolic processes and the effects of diet, nutrient deficiency, lifestyle, and microbiota composition. In present work, we focused on identifying age-related changes in organic acids in urine, and c...

A pilot evaluation of school-based LEGO® robotics therapy for autistic students.

Disability and rehabilitation. Assistive technology
There is emerging evidence that LEGO® therapy is an effective way of supporting younger autistic children develop their communication and social skills. LEGO® robotics therapy - which uses the principles of LEGO® therapy applied to LEGO® robotics - m...

Prediction based on machine learning of tooth sensitivity for in-office dental bleaching.

Journal of dentistry
OBJECTIVE: To develop a supervised machine learning model to predict the occurrence and intensity of tooth sensitivity (TS) in patients undergoing in-office dental bleaching testing various algorithm models.

When the bot walks the talk: Investigating the foundations of trust in an artificial intelligence (AI) chatbot.

Journal of experimental psychology. General
The concept of trust in artificial intelligence (AI) has been gaining increasing relevance for understanding and shaping human interaction with AI systems. Despite a growing literature, there are disputes as to whether the processes of trust in AI ar...

Detection of three-rooted mandibular first molars on panoramic radiographs using deep learning.

Scientific reports
This study aimed to develop a deep learning system for the detection of three-rooted mandibular first molars (MFMs) on panoramic radiographs and to assess its diagnostic performance. Panoramic radiographs, together with cone beam computed tomographic...

Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.

BMJ health & care informatics
OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection of paediatric appendicular fractures with and without the help of a commercially available fracture detection artificial intelligence (AI) solution i...

Signed Curvature Graph Representation Learning of Brain Networks for Brain Age Estimation.

IEEE journal of biomedical and health informatics
Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing impedes interactions between long-range nodes, hindering the ability of message-passing mechanism-bas...

Predicting adverse pregnancy outcome in Rwanda using machine learning techniques.

PloS one
BACKGROUND: Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contributing to morbidity, mortality, and long-term developmental challenges. This study aimed to predict these outcomes in Rwanda using supervised machine ...