AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Neuropsychological Tests

Showing 91 to 100 of 180 articles

Clear Filters

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 ...

Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework.

NeuroImage. Clinical
Investigation of the brain's functional connectome can improve our understanding of how an individual brain's organizational changes influence cognitive function and could result in improved individual risk stratification. Brain connectome studies in...

Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls.

Brain topography
Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Mult...

Higher Serum Endocan Level Is Associated with Alzheimer Disease.

Dementia and geriatric cognitive disorders
BACKGROUND: The novel molecule endocan, which is released by endothelium and is regulated by proangiogenic and proinflammatory cytokines, may have a role in the pathophysiology of Alzheimer disease (AD). The aim of this study was to evaluate the rela...