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Neuropsychological Tests

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Utility of MemTrax and Machine Learning Modeling in Classification of Mild Cognitive Impairment.

Journal of Alzheimer's disease : JAD
BACKGROUND: The widespread incidence and prevalence of Alzheimer's disease and mild cognitive impairment (MCI) has prompted an urgent call for research to validate early detection cognitive screening and assessment.

Machine-Learning Algorithms Based on Screening Tests for Mild Cognitive Impairment.

American journal of Alzheimer's disease and other dementias
BACKGROUND: The mobile screening test system for mild cognitive impairment (mSTS-MCI) was developed and validated to address the low sensitivity and specificity of the Montreal Cognitive Assessment (MoCA) widely used clinically.

Classification of Alzheimer's Disease with Respect to Physiological Aging with Innovative EEG Biomarkers in a Machine Learning Implementation.

Journal of Alzheimer's disease : JAD
BACKGROUND: Several studies investigated clinical and instrumental differences to make diagnosis of dementia in general and in Alzheimer's disease (AD) in particular with the aim to classify, at the individual level, AD patients and healthy controls ...

Using Machine Learning to Predict Dementia from Neuropsychiatric Symptom and Neuroimaging Data.

Journal of Alzheimer's disease : JAD
BACKGROUND: Machine learning (ML) is a promising technique for patient-specific prediction of mild cognitive impairment (MCI) and dementia development. Neuropsychiatric symptoms (NPS) might improve the accuracy of ML models but have barely been used ...

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques.

Journal of Alzheimer's disease : JAD
BACKGROUND: Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting Aβ positivity prior to PET ima...

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...