AIMC Topic: Adolescent

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Detecting abnormal electroencephalograms using deep convolutional networks.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVES: Electroencephalography (EEG) is a central part of the medical evaluation for patients with neurological disorders. Training an algorithm to label the EEG normal vs abnormal seems challenging, because of EEG heterogeneity and dependence of...

Brain dynamics and temporal trajectories during task and naturalistic processing.

NeuroImage
Human functional Magnetic Resonance Imaging (fMRI) data are acquired while participants engage in diverse perceptual, motor, cognitive, and emotional tasks. Although data are acquired temporally, they are most often treated in a quasi-static manner. ...

Ossification area localization in pediatric hand radiographs using deep neural networks for object detection.

PloS one
BACKGROUND: Detection of ossification areas of hand bones in X-ray images is an important task, e.g. as a preprocessing step in automated bone age estimation. Deep neural networks have emerged recently as de facto standard detection methods, but thei...

Social Conformity Effects on Trust in Simulation-Based Human-Robot Interaction.

Human factors
OBJECTIVE: We investigated the co-acting influences of communication and social conformity on trust in human-robot interaction.

Machine learning of brain gray matter differentiates sex in a large forensic sample.

Human brain mapping
Differences between males and females have been extensively documented in biological, psychological, and behavioral domains. Among these, sex differences in the rate and typology of antisocial behavior remains one of the most conspicuous and enduring...

Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Cerebral palsy (CP) is the most common physical disability among children (2.5 to 3.6 cases per 1000 live births). Inadequate physical activity (PA) is a major problem effecting the health and well-being of children with CP. Practical, ye...

A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography.

Dento maxillo facial radiology
OBJECTIVES:: The distal root of the mandibular first molar occasionally has an extra root, which can directly affect the outcome of endodontic therapy. In this study, we examined the diagnostic performance of a deep learning system for classification...

Frameless robot-assisted stereoelectroencephalography for refractory epilepsy in pediatric patients: accuracy, usefulness, and technical issues.

Acta neurochirurgica
BACKGROUND: Stereoelectroencephalography (SEEG) is an effective technique to help to locate and to delimit the epileptogenic area and/or to define relationships with functional cortical areas. We intend to describe the surgical technique and verify t...

Estimation of Neonatal Intestinal Perforation Associated with Necrotizing Enterocolitis by Machine Learning Reveals New Key Factors.

International journal of environmental research and public health
Intestinal perforation (IP) associated with necrotizing enterocolitis (NEC) is one of the leading causes of mortality in premature neonates; with major nutritional and neurodevelopmental sequelae. Since predicting which neonates will develop perforat...

Learning Curve in Robot-Assisted Laparoscopic Liver Resection.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: The objective of this study was to evaluate the learning curve effect on the safety and feasibility of robot-assisted liver resection (RALR).