AIMC Topic: Adolescent

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Automated Ventricular System Segmentation in Paediatric Patients Treated for Hydrocephalus Using Deep Learning Methods.

BioMed research international
Hydrocephalus is a common neurological condition that can have traumatic ramifications and can be lethal without treatment. Nowadays, during therapy radiologists have to spend a vast amount of time assessing the volume of cerebrospinal fluid (CSF) by...

Using Recurrent Neural Networks to Compare Movement Patterns in ADHD and Normally Developing Children Based on Acceleration Signals from the Wrist and Ankle.

Sensors (Basel, Switzerland)
Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental condition that affects, among other things, the movement patterns of children suffering it. Inattention, hyperactivity and impulsive behaviors, major symptoms characterizing ...

Application of machine learning to structural connectome to predict symptom reduction in depressed adolescents with cognitive behavioral therapy (CBT).

NeuroImage. Clinical
PURPOSE: Adolescent major depressive disorder (MDD) is a highly prevalent, incapacitating and costly illness. Many depressed teens do not improve with cognitive behavioral therapy (CBT), a first-line treatment for adolescent MDD, and face devastating...

Neural Mechanisms for Accepting and Rejecting Artificial Social Partners in the Uncanny Valley.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Artificial agents are becoming prevalent across human life domains. However, the neural mechanisms underlying human responses to these new, artificial social partners remain unclear. The uncanny valley (UV) hypothesis predicts that humans prefer anth...

Using machine learning to examine the relationship between asthma and absenteeism.

Environmental monitoring and assessment
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating ...

Harnessing robotic automation and web-based technologies to modernize scientific outreach.

PLoS biology
Technological breakthroughs in the past two decades have ushered in a new era of biomedical research, turning it into an information-rich and technology-driven science. This scientific revolution, though evident to the research community, remains opa...

Anatomical context improves deep learning on the brain age estimation task.

Magnetic resonance imaging
Deep learning has shown remarkable improvements in the analysis of medical images without the need for engineered features. In this work, we hypothesize that deep learning is complementary to traditional feature estimation. We propose a network desig...

Effect of EMG-biofeedback robotic-assisted body weight supported treadmill training on walking ability and cardiopulmonary function on people with subacute spinal cord injuries - a randomized controlled trial.

BMC neurology
BACKGROUND: Body weight supported treadmill training (BWSTT) is a frequently used approach for restoring the ability to walk after spinal cord injury (SCI). However, the duration of BWSTT is usually limited by fatigue of the therapists and patients. ...