Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]

Simfukwe C, An SSA, Youn YC. Neuropsychiatr Dis Treat. 2024;20:2375—2389. The authors have advised that the funding statement on page 2387 is incorrect. The correct statement should read as follows. FundingThis research was supported by the Cooperative Research Program for Agriculture Sci...

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Main Authors: Simfukwe C, An SSA, Youn YC
Format: Article
Language:English
Published: Dove Medical Press 2024-12-01
Series:Neuropsychiatric Disease and Treatment
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Online Access:https://www.dovepress.com/corrigendum-contribution-of-scalp-regions-to-machine-learning-based-cl-peer-reviewed-fulltext-article-NDT
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author Simfukwe C
An SSA
Youn YC
author_facet Simfukwe C
An SSA
Youn YC
author_sort Simfukwe C
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description Simfukwe C, An SSA, Youn YC. Neuropsychiatr Dis Treat. 2024;20:2375—2389. The authors have advised that the funding statement on page 2387 is incorrect. The correct statement should read as follows. FundingThis research was supported by the Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01712403) Rural Development Administration, Republic of Korea, and a basic science research program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00251396 and 2021R1A6A1A03038996). The authors apologize for this error.
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spelling doaj-art-503d615a0a5f432faa3bc0092f401b9c2025-08-20T01:59:43ZengDove Medical PressNeuropsychiatric Disease and Treatment1178-20212024-12-01Volume 202569257098572Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]Simfukwe CAn SSAYoun YCSimfukwe C, An SSA, Youn YC. Neuropsychiatr Dis Treat. 2024;20:2375—2389. The authors have advised that the funding statement on page 2387 is incorrect. The correct statement should read as follows. FundingThis research was supported by the Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01712403) Rural Development Administration, Republic of Korea, and a basic science research program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00251396 and 2021R1A6A1A03038996). The authors apologize for this error.https://www.dovepress.com/corrigendum-contribution-of-scalp-regions-to-machine-learning-based-cl-peer-reviewed-fulltext-article-NDTelectroencephalographyeyes-openeyes-closequantitativemachine learningalzheimer's diseasemild cognitive impairmentpower spectrum density.
spellingShingle Simfukwe C
An SSA
Youn YC
Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]
Neuropsychiatric Disease and Treatment
electroencephalography
eyes-open
eyes-close
quantitative
machine learning
alzheimer's disease
mild cognitive impairment
power spectrum density.
title Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]
title_full Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]
title_fullStr Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]
title_full_unstemmed Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]
title_short Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals [Corrigendum]
title_sort contribution of scalp regions to machine learning based classification of dementia utilizing resting state qeeg signals corrigendum
topic electroencephalography
eyes-open
eyes-close
quantitative
machine learning
alzheimer's disease
mild cognitive impairment
power spectrum density.
url https://www.dovepress.com/corrigendum-contribution-of-scalp-regions-to-machine-learning-based-cl-peer-reviewed-fulltext-article-NDT
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