AIMC Topic: Adolescent

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Controlling robots in the home: Factors that affect the performance of novice robot operators.

Applied ergonomics
For robots to successfully integrate into everyday life, it is important that they can be effectively controlled by laypeople. However, the task of manually controlling mobile robots can be challenging due to demanding cognitive and sensorimotor requ...

Knowledge-based reconstruction for measurement of right ventricular volumes on cardiovascular magnetic resonance images in a mixed population.

Congenital heart disease
OBJECTIVE: Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observer-dependency of manual analysis of right ventricular volume...

Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis.

Schizophrenia research
OBJECTIVE: Structural and functional abnormalities have been reported in the brain of patients with adolescent-onset schizophrenia (AOS). The brain regional functional synchronization in patients with AOS remains unclear.

Robotic Resistance Treadmill Training Improves Locomotor Function in Children With Cerebral Palsy: A Randomized Controlled Pilot Study.

Archives of physical medicine and rehabilitation
OBJECTIVE: To determine whether applying controlled resistance forces to the legs during the swing phase of gait may improve the efficacy of treadmill training as compared with applying controlled assistance forces in children with cerebral palsy (CP...

DCE-MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro-fuzzy-based model and nested model selection technique.

NMR in biomedicine
This pilot study investigates the construction of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimat...

Classification of Paediatric Inflammatory Bowel Disease using Machine Learning.

Scientific reports
Paediatric inflammatory bowel disease (PIBD), comprising Crohn's disease (CD), ulcerative colitis (UC) and inflammatory bowel disease unclassified (IBDU) is a complex and multifactorial condition with increasing incidence. An accurate diagnosis of PI...

Robot-assisted thoracoscopic lobectomy as treatment of a giant bulla.

Journal of cardiothoracic surgery
BACKGROUND: A bulla is a marked enlarged space within the parenchyma of the lung. Bullae may cause dyspnea by compressing healthy lung parenchyma and can cause a pneumothorax. Also, bullae are associated with malignancy, therefore surgical bullectomy...

Personalized Age Progression with Bi-Level Aging Dictionary Learning.

IEEE transactions on pattern analysis and machine intelligence
Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a personalized way. Basically, for each age group, we learn an aging diction...

Crowdsourced validation of a machine-learning classification system for autism and ADHD.

Translational psychiatry
Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) together affect >10% of the children in the United States, but considerable behavioral overlaps between the two disorders can often complicate differential diagnosis. ...

The potential impact of the hypovitaminosis D on metabolic complications in obese adolescents - Preliminary results.

Annals of agricultural and environmental medicine : AAEM
INTRODUCTION AND OBJECTIVE: Vitamin D deficiency is common in obesity; however, its contribution in the development of metabolic complications remains uncertain. The aim of the study was to examine the relationships between vitamin D status and metab...