AIMC Topic: Neuropsychological Tests

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Predicting amyloid beta accumulation in cognitively unimpaired older adults: Cognitive assessments provide no additional utility beyond demographic and genetic factors.

Alzheimer's & dementia : the journal of the Alzheimer's Association
BACKGROUND: Integrating non-invasive measures to estimate abnormal amyloid beta accumulation (Aβ+) is key to developing a screening tool for preclinical Alzheimer's disease (AD). The predictive capability of standard neuropsychological tests in estim...

Evaluating AI Models: Performance Validation Using Formal Multiple-Choice Questions in Neuropsychology.

Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists
High-quality and accessible education is crucial for advancing neuropsychology. A recent study identified key barriers to board certification in clinical neuropsychology, such as time constraints and insufficient specialized knowledge. To address the...

Transforming text to music using artificial intelligence improves the frontal lobe function of normal older adults.

Brain and behavior
INTRODUCTION: Recent advances in artificial intelligence (AI) have been substantial. We investigated the effectiveness of an online meeting in which normal older adults (otokai) used a music-generative AI that transforms text to music (Music Trinity ...

A Regression Framework for Predicting Cognitive Decline in Frontotemporal Dementia using Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Frontotemporal dementia (FTD) is a progressive neurodegenerative disorder with a diverse range of symptoms, including personality changes, behavioral disturbances, language deficits, and impaired executive functions. FTD has three main subtypes: beha...

Identification of Dementia & Mild Cognitive Impairment in Chinese Elderly Using Machine Learning.

American journal of Alzheimer's disease and other dementias
OBJECTIVE: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment.

Updated Models of Alzheimer's Disease with Deep Neural Networks.

Journal of Alzheimer's disease : JAD
BACKGROUND: In recent years, researchers have focused on developing precise models for the progression of Alzheimer's disease (AD) using deep neural networks. Forecasting the progression of AD through the analysis of time series data represents a pro...

Simplifying Alzheimer's Disease Monitoring: A Novel Machine-Learning Approach to Estimate the Clinical Dementia Rating Sum of Box Changes Using the Mini-Mental State Examination and Functional Activities Questionnaire.

Journal of Alzheimer's disease : JAD
BACKGROUND: Primary outcome measure in the clinical trials of disease modifying therapy (DMT) drugs for Alzheimer's disease (AD) has often been evaluated by Clinical Dementia Rating sum of boxes (CDRSB). However, CDR testing requires specialized trai...

Cognitive Screening for Mild Cognitive Impairment: Clinician Perspectives on Current Practices and Future Directions.

Journal of Alzheimer's disease : JAD
 This study surveyed 51 specialist clinicians for their views on existing cognitive screening tests for mild cognitive impairment and their opinions about a hypothetical remote screener driven by artificial intelligence (AI). Responses revealed signi...

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.