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Related Concept Videos

Dementia01:30

Dementia

109
Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....
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Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

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Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
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Cognitive Development During Adulthood01:30

Cognitive Development During Adulthood

73
Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
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Related Experiment Video

Updated: Jun 18, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Using Deep Learning Techniques as an Attempt to Create the Most Cost-Effective Screening Tool for Cognitive Decline.

Hye-Geum Kim1, Wan-Seok Seo1, Bon-Hoon Koo1

  • 1Department of Psychiatry, Yeungnam University College of Medicine, Yeungnam University Medical Center, Daegu, Republic of Korea.

Psychiatry Investigation
|August 1, 2024
PubMed
Summary
This summary is machine-generated.

Deep learning models can effectively screen for cognitive decline, a precursor to Alzheimer's disease (AD). This approach uses neuropsychological tests to improve early AD diagnostics and detection.

Keywords:
CognitionDeep learningDementiaNeuropsychology

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Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Gerontology

Background:

  • Cognitive decline is an early indicator of Alzheimer's disease (AD).
  • Early detection of cognitive decline is crucial for timely intervention and management.
  • Developing accessible and cost-effective screening tools is essential for widespread use.

Purpose of the Study:

  • To develop a cost-effective and accessible deep learning (DL) screening tool for cognitive decline.
  • To improve the early detection of Alzheimer's disease (AD) precursors.
  • To integrate demographic variables into neuropsychological testing for personalized assessment.

Main Methods:

  • Utilized a dataset of 2,863 subjects with subjective cognitive complaints.
  • Employed a random forest classifier to identify predictive neuropsychological test combinations.
  • Trained and validated the DL model, focusing on feature importance for cognitive decline indicators.

Main Results:

  • The DL model achieved 82.42% accuracy and an 0.816 area under the curve for dementia classification.
  • Identified key cognitive domains and tests: attention (TMT-B), language (BNT), memory (RCFT delayed recall), visuospatial skills (RCFT copy), and frontal function (Stroop).
  • Demographic variables (age, sex, education) were adjusted for in the comprehensive assessment.

Conclusions:

  • Deep learning shows significant potential for enhancing Alzheimer's disease (AD) diagnostics.
  • A comprehensive battery of cognitive assessments, analyzed via DL, may offer superior diagnostic accuracy.
  • This study provides a foundation for refining DL-based screening tools for broader clinical application.