AIMC Topic: Child

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Convolutional Neural Networks for Pediatric Refractory Epilepsy Classification Using Resting-State Functional Magnetic Resonance Imaging.

World neurosurgery
OBJECTIVE: This study aims to evaluate the performance of convolutional neural networks (CNNs) trained with resting-state functional magnetic resonance imaging (rfMRI) latency data in the classification of patients with pediatric epilepsy from health...

Automated Lateral Ventricular and Cranial Vault Volume Measurements in 13,851 Patients Using Deep Learning Algorithms.

World neurosurgery
BACKGROUND: No large dataset-derived standard has been established for normal or pathologic human cerebral ventricular and cranial vault volumes. Automated volumetric measurements could be used to assist in diagnosis and follow-up of hydrocephalus or...

Gender Stereotypes in Natural Language: Word Embeddings Show Robust Consistency Across Child and Adult Language Corpora of More Than 65 Million Words.

Psychological science
Stereotypes are associations between social groups and semantic attributes that are widely shared within societies. The spoken and written language of a society affords a unique way to measure the magnitude and prevalence of these widely shared colle...

Magnetically actuated intelligent hydrogel-based child-parent microrobots for targeted drug delivery.

Journal of materials chemistry. B
Small intestine-targeted drug delivery by oral administration has aroused the growing interest of researchers. In this work, the child-parent microrobot (CPM) as a vehicle protects the child microrobots (CMs) under a gastric acid environment and rele...

Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.

IEEE journal of biomedical and health informatics
The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and ...

Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.

PloS one
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...

The Potential and the Limitations of Esophageal Robotic Surgery in Children.

European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie
INTRODUCTION:  There have been numerous reports of robotic pediatric surgery in the literature, particularly regarding urological procedures for school-aged children. Thoracic procedures appear to be less common, despite the fact that encouraging res...

Kashin-Beck disease diagnosis based on deep learning from hand X-ray images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Kashin-Beck Disease (KBD) is a serious endemic bone disease leading to short stature. The early radiological examinations are crucial for potential patients. However, many children in rural China cannot be diagnosed in time ...