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Neuropsychological Tests

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A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

NeuroImage
Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algo...

Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional connectivity (FC) alterations during performance of tasks involving attention. As compared with SCZ, these alterations are present in SIB to a lesser exten...

Fractal dimension of cerebral white matter: A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment.

NeuroImage. Clinical
Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of the...

Identifying cognitive deficits in cocaine dependence using standard tests and machine learning.

Progress in neuro-psychopharmacology & biological psychiatry
There is a growing need to address the variability in detecting cognitive deficits with standard tests in cocaine dependence (CD). The aim of the current study was to identify cognitive deficits by means of Machine Learning (ML) algorithms: Generaliz...

EIQ: EEG based IQ test using wavelet packet transform and hierarchical extreme learning machine.

Journal of neuroscience methods
BACKGROUND: The use of electroencephalography has been perpetually incrementing and has numerous applications such as clinical and psychiatric studies, social interactions, brain computer interface etc. Intelligence has baffled us for centuries, and ...

Machine Learning Enhances the Efficiency of Cognitive Screenings for Primary Care.

Journal of geriatric psychiatry and neurology
BACKGROUND: Incorporation of cognitive screening into the busy primary care will require the development of highly efficient screening tools. We report the convergence validity of a very brief, self-administered, computerized assessment protocol agai...

Supervised machine learning to decipher the complex associations between neuro-immune biomarkers and quality of life in schizophrenia.

Metabolic brain disease
Stable phase schizophrenia is characterized by altered patterning in tryptophan catabolites (TRYCATs) and memory impairments, which are associated with PHEMN (psychosis, hostility, excitation, mannerism and negative) and DAPS (depression, anxiety and...

Social-cue perception and mentalizing ability following traumatic brain injury: A human-robot interaction study.

Brain injury
PRIMARY OBJECTIVE: Research studies and clinical observations of individuals with traumatic brain injury (TBI) indicate marked deficits in mentalizing-perceiving social information and integrating it into judgements about the affective and mental sta...