AIMC Topic: Adolescent

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Variability of automated carotid intima-media thickness measurements by novice operators.

Clinical physiology and functional imaging
Carotid intima-media thickness (C-IMT) measurements provide a non-invasive assessment of subclinical atherosclerosis. The aim of the study was to assess the inter- and intra-observer variability of automated C-IMT measurements undertaken by two novic...

Toward a tactile language for human-robot interaction: two studies of tacton learning and performance.

Human factors
OBJECTIVE: Two experiments were performed to investigate the feasibility for robot-to-human communication of a tactile language using a lexicon of standardized tactons (tactile icons) within a sentence.

A machine learning approach using auditory odd-ball responses to investigate the effect of Clozapine therapy.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball auditory evoked potentials to identify neurophysiologic changes induced by Clozapine (CLZ) treatment in responding schizophrenic (SCZ) subjects. This ...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

European child & adolescent psychiatry
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

Journal of neural transmission (Vienna, Austria : 1996)
While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do not translate into diagnostic value for the individual patient. Machine-learning generates predictiv...

Learning to manipulate and categorize in human and artificial agents.

Cognitive science
This study investigates the acquisition of integrated object manipulation and categorization abilities through a series of experiments in which human adults and artificial agents were asked to learn to manipulate two-dimensional objects that varied i...

Epileptic seizure prediction using relative spectral power features.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and to reduce the number of false alarms.

Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes.

IEEE journal of biomedical and health informatics
Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown that 50-80% proportion of T2DM is undiagnosed. In this paper, support vector machines are utilized to screen diabetes, and an ensemble learning module i...

Decoding objects of basic categories from electroencephalographic signals using wavelet transform and support vector machines.

Brain topography
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches conducted mainly for brain-computer interface applications. In this study we aimed to classify single-t...

Exploring Primary and Interaction Effects of Minor Physical Anomalies: Development and Validation of Prediction Models Using Explainable Machine Learning Algorithms for Early-Onset Schizophrenia.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Minor physical abnormalities (MPAs) are neurodevelopmental markers that can be traced to prenatal events and may be significant features of early-onset schizophrenia (EOS). Therefore, our study aimed to (1) find the primary...