Decoding Behavior: Utilizing Virtual Reality Digital Marker and Machine Learning for Early Detection of Mild Cognitive Impairment-Reference-Cited by-同舟云学术

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Decoding Behavior: Utilizing Virtual Reality Digital Marker and Machine Learning for Early Detection of Mild Cognitive Impairment

Published:2024-05-11 Issue: Volume: Page:1-8
ISSN:
Container-title:Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
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Author:

Kim Yuwon¹^ORCID,Park Jinseok²^ORCID,Choi Hojin²^ORCID,Loeser Martin³^ORCID,Ryu Hokyoung⁴^ORCID,Seo Kyoungwon¹^ORCID

Affiliation:

1. Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, Korea, Republic of

2. Department of Neurology, College of Medicine, Hanyang University, Korea, Republic of

3. Department of Computer Science, Electrical Engineering and Mechatronics, ZHAW Zurich University of Applied Sciences, Switzerland

4. Hanyang Universoty, Korea, Republic of

Funder

Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613905.3650731

Reference58 articles.

1. Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019

2. Cognitive assessment tools for mild cognitive impairment screening

3. Cerebrospinal fluid biomarker panel of synaptic dysfunction in Alzheimer's disease and other neurodegenerative disorders

4. Analysis of Features of Alzheimer’s Disease: Detection of Early Stage from Functional Brain Changes in Magnetic Resonance Images Using a Finetuned ResNet18 Network

5. EARLY DETECTION OF MILD COGNITIVE IMPAIRMENT (MCI) IN AN AT-HOME SETTING

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