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Neuropsychological Tests

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Effects of Exercise-Diet Therapy on Cognitive Function in Healthy Elderly People Evaluated by Deep Learning Based on Basic Blood Test Data.

Advances in experimental medicine and biology
BACKGROUND: Recent studies reported that vascular cognitive impairment in the elderly caused by arteriosclerosis plays an important role in cognitive disorders in both vascular dementia and Alzheimer's disease. In addition, systemic metabolic disorde...

Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records.

BMC medical informatics and decision making
BACKGROUND: Dementia develops as cognitive abilities deteriorate, and early detection is critical for effective preventive interventions. However, mainstream diagnostic tests and screening tools, such as CAMCOG and MMSE, often fail to detect dementia...

A machine-learning algorithm for predicting brain age using Rey-Osterrieth complex figure tests of healthy participants.

Applied neuropsychology. Adult
OBJECTIVE: Neuropsychologists widely use the Rey-Osterrieth complex figure test (RCFT) as part of neuropsychological test batteries to evaluate cognitive function and assess constructional ability, with age being the most significant factor. Our stud...

Application of machine learning techniques for dementia severity prediction from psychometric tests in the elderly population.

Applied neuropsychology. Adult
Previous research has shown the benefits of early detection and treatment of dementia. This detection is usually performed manually by one or more clinicians based on reports and psychometric testing. Machine learning algorithms provide an alternativ...

Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands.

Scientific reports
The clock drawing test is a simple and inexpensive method to screen for cognitive frailties, including dementia. In this study, we used the relevance factor variational autoencoder (RF-VAE), a deep generative neural network, to represent digitized cl...

Feature extraction of time series data on functional near-infrared spectroscopy and comparison of deep learning performance for classifying patients with Alzheimer's-related mild cognitive impairment: a post-hoc analysis of a diagnostic interventional trial.

European review for medical and pharmacological sciences
OBJECTIVE: This study aimed to define a method of classifying patients with mild cognitive impairment caused by Alzheimer's disease by the retrieval of functional near-infrared spectroscopy (fNIRS) signal characteristics obtained during olfactory sti...

Using Artificial Intelligence to Identify the Associations of Children's Performance of Coloring, Origami, and Copying Activities With Visual-Motor Integration.

The American journal of occupational therapy : official publication of the American Occupational Therapy Association
IMPORTANCE: Performance of coloring, origami, and copying activities reflects children's visual-motor integration (VMI), but the levels of association remain unclear.

Robotic assessment of sensorimotor and cognitive deficits in patients with temporal lobe epilepsy.

Epilepsy & behavior : E&B
OBJECTIVE: Individuals with temporal lobe epilepsy (TLE) frequently demonstrate impairments in executive function, working memory, and/or declarative memory. It is recommended that screening for cognitive impairment is undertaken in all people newly ...

Predictive deep learning models for cognitive risk using accessible data.

Bioscience trends
The early detection of mild cognitive impairment (MCI) is crucial to preventing the progression of dementia. However, it necessitates that patients voluntarily undergo cognitive function tests, which may be too late if symptoms are only recognized on...

Machine-based learning of multidimensional data in bipolar disorder - pilot results.

Bipolar disorders
INTRODUCTION: Owing to the heterogenic picture of bipolar disorder, it takes approximately 8.8 years to reach a correct diagnosis. Early recognition and early intervention might not only increase quality of life, but also increase life expectancy as ...