AIMC Topic: Neuropsychological Tests

Clear Filters Showing 1 to 10 of 205 articles

Evaluating AI chatbots in neurological function test interpretation for brain tumor surgery.

Neurosurgical review
Neuropsychological assessments are essential for evaluating functional status and guiding surgical planning in patients with brain tumors. However, their complexity may hinder interpretation for patients and junior clinicians. Large language model (L...

Machine learning-based estimation of the mild cognitive impairment stage using multimodal physical and behavioral measures.

Scientific reports
Mild cognitive impairment (MCI) is a prodromal stage of dementia, and its early detection is critical for improving clinical outcomes. However, current diagnostic tools such as brain magnetic resonance imaging (MRI) and neuropsychological testing hav...

Understanding the relationship between rosemary odor and mental workload through deep learning.

Neuroscience
This research explores the novel application of aromatic odors, specifically rosemary, in reducing mental workload, employing deep learning methods to analyze electroencephalogram (EEG) signals without feature extraction. Thirty volunteers participat...

Handwriting in Mild Cognitive Impairment: Reliability Assessment and Machine Learning-Based Screening.

JMIR aging
BACKGROUND: Mild cognitive impairment (MCI) is a precursor of dementia. Therefore, MCI identification and monitoring are crucial to delaying dementia onset. Given the limits of existing clinical tests, objective support tools are needed.

Neural correlates of metacognition in education: a machine learning approach.

Neuropsychologia
Metacognition, the ability to reflect and regulate one's cognitive processes, has been shown to play a role in various aspects of life, particularly in academic settings. While important steps have been made in uncovering the neural basis of metacogn...

Data-driven cognitive subtypes in major depressive disorder: Grey matter atrophy in the left fusiform gyrus and cerebellum.

Journal of affective disorders
BACKGROUND: This study aims to apply a semi-supervised machine learning approach for classifying major depressive disorder (MDD) patients into more homogeneous cognitive subtypes based on multidimensional cognitive profiles, and to perform multimodal...

Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review.

JMIR mental health
BACKGROUND: Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive systems (GISs) ...

Machine Learning-Based Cognitive Assessment With The Autonomous Cognitive Examination: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive assessments. The Autonomous Cognitive Examination (ACoE) is a foundational cognitive test for the phenotyping of cognitive symptoms across the primary cogniti...

Multi-modal predictive modeling of schizophrenia severity: Leveraging liver function indicators and cognitive scores with random forest and SVM.

Psychiatry research. Neuroimaging
Schizophrenia is a complex neuropsychiatric disorder with cognitive deficits and systemic physiological disturbances, including emerging links to hepatic dysfunction via the gut-liver-brain axis. Despite growing evidence, the integration of liver fun...