AIMC Topic: Adolescent

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Prediction of gender from longitudinal MRI data via deep learning on adolescent data reveals unique patterns associated with brain structure and change over a two-year period.

Journal of neuroscience methods
Deep learning algorithms for predicting neuroimaging data have shown considerable promise in various applications. Prior work has demonstrated that deep learning models that take advantage of the data's 3D structure can outperform standard machine le...

Dynamic prediction of life-threatening events for patients in intensive care unit.

BMC medical informatics and decision making
BACKGROUND: Early prediction of patients' deterioration is helpful in early intervention for patients at greater risk of deterioration in Intensive Care Unit (ICU). This study aims to apply machine learning approaches to heterogeneous clinical data f...

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction.

Scientific reports
The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is de...

An artificial-intelligence-based age-specific template construction framework for brain structural analysis using magnetic resonance images.

Human brain mapping
It is an essential task to construct brain templates and analyze their anatomical structures in neurological and cognitive science. Generally, templates constructed from magnetic resonance imaging (MRI) of a group of subjects can provide a standard r...

Completion of disconnective surgery for refractory epilepsy in pediatric patients using robot-assisted MRI-guided laser interstitial thermal therapy.

Journal of neurosurgery. Pediatrics
OBJECTIVE: Since 2007, the authors have performed 34 hemispherotomies and 17 posterior quadrant disconnections (temporoparietooccipital [TPO] disconnections) for refractory epilepsy at Sant Joan de Déu Barcelona Children's Hospital. Incomplete discon...

Brain Age Prediction: A Comparison between Machine Learning Models Using Brain Morphometric Data.

Sensors (Basel, Switzerland)
Brain structural morphology varies over the aging trajectory, and the prediction of a person's age using brain morphological features can help the detection of an abnormal aging process. Neuroimaging-based brain age is widely used to quantify an indi...

Thyroid Nodules on Ultrasound in Children and Young Adults: Comparison of Diagnostic Performance of Radiologists' Impressions, ACR TI-RADS, and a Deep Learning Algorithm.

AJR. American journal of roentgenology
In current clinical practice, thyroid nodules in children are generally evaluated on the basis of radiologists' overall impressions of ultrasound images. The purpose of this article is to compare the diagnostic performance of radiologists' overall ...

DENSEN: a convolutional neural network for estimating chronological ages from panoramic radiographs.

BMC bioinformatics
BACKGROUND: Age estimation from panoramic radiographs is a fundamental task in forensic sciences. Previous age assessment studies mainly focused on juvenile rather than elderly populations (> 25 years old). Most proposed studies were statistical or s...

A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy-Which markers work best for which gait patterns?

PloS one
Neuromotor pathologies often cause motor deficits and deviations from typical locomotion, reducing the quality of life. Clinical gait analysis is used to effectively classify these motor deficits to gain deeper insights into resulting walking behavio...

Exploration of Variables Predicting Sense of School Belonging Using the Machine Learning Method-Group Mnet.

Psychological reports
The purpose of this study was to explore variables related to school belonging from a holistic perspective, including a large number of variables in one model, different to the traditional analytical method. Using 2015 data from the Program for Inter...