AIMC Topic: Neuropsychological Tests

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Deep Learning Analysis of Cerebral Blood Flow to Identify Cognitive Impairment and Frailty in Persons Living With HIV.

Journal of acquired immune deficiency syndromes (1999)
BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairment and frailty in people living with HIV (PLWH). Feature extraction techniques identified brain regions that were the strongest predictors.

Identification and evaluation of cognitive deficits in schizophrenia using "Machine learning".

Psychiatria Danubina
BACKGROUND: Schizophrenia can be interpreted as a pathology involving the neocortex whose cognitive dysfunctions represent a central and persistent characteristic of the disease, as well as one of the more important symptoms in relation to the impair...

Robot Diagnosis Test for Egocentric and Allocentric Hemineglect.

Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists
OBJECTIVE: Patients with hemineglect fail to respond to egocentric stimuli or allocentric parts of stimuli contralateral to the brain lesion. The clinical diagnosis of hemineglect mainly involves evaluation of the egocentric form, while less sensitiv...

The Effectiveness of the Game of Dice Task in Predicting At-Risk and Problem Gambling Among Adolescents: The Contribution of the Neural Networks.

Journal of gambling studies
The Game of Dice Task (GDT; Brand et al. in Neuropsychology 19:267-277, 2005a; Psychiatry Res 133:91-99, 2005b) measures decision-making under objective risk conditions. Although disadvantageous decision-making has been shown in individuals with subs...

Artificial Neural Networks Help to Better Understand the Interplay Between Cognition, Mediterranean Diet, and Physical Performance: Clues from TRELONG Study.

Journal of Alzheimer's disease : JAD
BACKGROUND: Nutrition plays an important role in the aging process. Adherence to the Mediterranean diet (MedDiet) has been shown to be associated with lower rates of diseases. Cognitive status seems to be strongly interrelated with physical well-bein...

Detecting Alzheimer's Disease from Continuous Speech Using Language Models.

Journal of Alzheimer's disease : JAD
BACKGROUND: Recently, many studies have been carried out to detect Alzheimer's disease (AD) from continuous speech by linguistic analysis and modeling. However, few of them utilize language models (LMs) to extract linguistic features and to investiga...

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification.

Journal of Alzheimer's disease : JAD
BACKGROUND: Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient manage...

Automated Rating of Multiple Sclerosis Test Results Using a Convolutional Neural Network.

Studies in health technology and informatics
This work concerns methods for automated rating of the progression of Multiple Sclerosis (MS). Often, MS patients develop cognitive deficits. The Brief Visuospatial Memory Test-Revised (BVMT-R) is a recognized method to measure optical recognition de...

Use of Machine Learning to Determine Deviance in Neuroanatomical Maturity Associated With Future Psychosis in Youths at Clinically High Risk.

JAMA psychiatry
IMPORTANCE: Altered neurodevelopmental trajectories are thought to reflect heterogeneity in the pathophysiologic characteristics of schizophrenia, but whether neural indicators of these trajectories are associated with future psychosis is unclear.