AIMC Topic: Child

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Real-time multi-channel monitoring of burst-suppression using neural network technology during pediatric status epilepticus treatment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To develop a real-time monitoring system that has the potential to guide the titration of anesthetic agents in the treatment of pediatric status epilepticus (SE).

Evaluation of the effectiveness of robotic gait training and gait-focused physical therapy programs for children and youth with cerebral palsy: a mixed methods RCT.

BMC neurology
BACKGROUND: Robot assisted gait training (RAGT) is considered to be a promising approach for improving gait-related gross motor function of children and youth with cerebral palsy. However, RAGT has yet to be empirically demonstrated to be effective. ...

Diagnostic Classification of ADHD Versus Control: Support Vector Machine Classification Using Brief Neuropsychological Assessment.

Journal of attention disorders
Common methods for clinical diagnosis include clinical interview, behavioral questionnaires, and neuropsychological assessment. These methods rely on clinical interpretation and have variable reliability, sensitivity, and specificity. The goal of th...

A framework for the automatic detection and characterization of brain malformations: Validation on the corpus callosum.

Medical image analysis
In this paper, we extend the one-class Support Vector Machine (SVM) and the regularized discriminative direction analysis to the Multiple Kernel (MK) framework, providing an effective analysis pipeline for the detection and characterization of brain ...

Neural correlates of consciousness in patients who have emerged from a minimally conscious state: a cross-sectional multimodal imaging study.

The Lancet. Neurology
BACKGROUND: Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in which patients regain the capacity for functional communicati...

Will they participate? Predicting patients' response to clinical trial invitations in a pediatric emergency department.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: (1) To develop an automated algorithm to predict a patient's response (ie, if the patient agrees or declines) before he/she is approached for a clinical trial invitation; (2) to assess the algorithm performance and the predictors on real-w...

Using assistive robots to promote inclusive education.

Disability and rehabilitation. Assistive technology
PURPOSE: This paper describes the development and test of physical and virtual integrated augmentative manipulation and communication assistive technologies (IAMCATs) that enable children with motor and speech impairments to manipulate educational it...

Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent behavioral disorders in childhood and adolescence. Recently, network-based diagnosis of ADHD has attracted great attentions due to the fact that ADHD disease is ...

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum d...