AIMC Topic: Child

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Population Graph-Based Multi-Model Ensemble Method for Diagnosing Autism Spectrum Disorder.

Sensors (Basel, Switzerland)
With the advancement of brain imaging techniques and a variety of machine learning methods, significant progress has been made in brain disorder diagnosis, in particular Autism Spectrum Disorder. The development of machine learning models that can di...

Predicting brain age with complex networks: From adolescence to adulthood.

NeuroImage
In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brai...

[Leptin sexual dimorphism, insulin resistance, and body composition in normal weight prepubescent].

Revista chilena de pediatria
INTRODUCTION: The prepubertal stage is a critical period of body fat development, in which leptin and insulin re sistance has been associated, however, there are few studies in normal-weight prepubescents. Ob jective: To assess the relationship betwe...

Introducing the NEMO-Lowlands iconic gesture dataset, collected through a gameful human-robot interaction.

Behavior research methods
This paper describes a novel dataset of iconic gestures, together with a publicly available robot-based elicitation method to record these gestures, which consists of playing a game of charades with a humanoid robot. The game was deployed at a scienc...

Can artificial intelligence achieve human-level performance? A pilot study of childhood sexual abuse detection in self-figure drawings.

Child abuse & neglect
Childhood sexual abuse (CSA) is a worldwide phenomenon that has negative long-term consequences for the victims and their families, and inflicts a considerable economic toll on society. One of the main difficulties in treating CSA is victims' relucta...

Deep learning-based method for reducing residual motion effects in diffusion parameter estimation.

Magnetic resonance in medicine
PURPOSE: Conventional motion-correction techniques for diffusion MRI can introduce motion-level-dependent bias in derived metrics. To address this challenge, a deep learning-based technique was developed to minimize such residual motion effects.

Ordered interpersonal synchronisation in ASD children via robots.

Scientific reports
Children with autistic spectrum disorders (ASD) experience persistent disrupted coordination in interpersonal synchronisation that is thought to be associated with deficits in neural connectivity. Robotic interventions have been explored for use with...

Diagnosis of common pulmonary diseases in children by X-ray images and deep learning.

Scientific reports
Acute lower respiratory infection is the leading cause of child death in developing countries. Current strategies to reduce this problem include early detection and appropriate treatment. Better diagnostic and therapeutic strategies are still needed ...

Violence detection explanation via semantic roles embeddings.

BMC medical informatics and decision making
BACKGROUND: Emergency room reports pose specific challenges to natural language processing techniques. In this setting, violence episodes on women, elderly and children are often under-reported. Categorizing textual descriptions as containing violenc...

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

Epilepsia
OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessm...