AIMC Topic: Neuropsychological Tests

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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...

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.

BMC geriatrics
BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a ne...

Machine learning as a new paradigm for characterizing localization and lateralization of neuropsychological test data in temporal lobe epilepsy.

Epilepsy & behavior : E&B
In this study, we employed a kernel support vector machine to predict epilepsy localization and lateralization for patients with a diagnosis of epilepsy (n = 228). We assessed the accuracy to which indices of verbal memory, visual memory, verbal flue...

Assessing ADHD symptoms in children and adults: evaluating the role of objective measures.

Behavioral and brain functions : BBF
BACKGROUND: Diagnostic guidelines recommend using a variety of methods to assess and diagnose ADHD. Applying subjective measures always incorporates risks such as informant biases or large differences between ratings obtained from diverse sources. Fu...

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network.

Computational intelligence and neuroscience
Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain-computer interface applications, but subjects who do not sho...

Test-retest reliability of the KINARM end-point robot for assessment of sensory, motor and neurocognitive function in young adult athletes.

PloS one
BACKGROUND: Current assessment tools for sport-related concussion are limited by a reliance on subjective interpretation and patient symptom reporting. Robotic assessments may provide more objective and precise measures of neurological function than ...