Publication Name	World Journal of Psychiatry
Manuscript ID	69315
Country	South Korea

Category	Psychiatry
Manuscript Type	Editorial
Article Title	Screening dementia and predicting high dementia risk groups using machine learning
Manuscript Source	Invited Manuscript
All Author List	Haewon Byeon
Funding Agency and Grant Number	Funding Agency Grant Number National Research Foundation of Korea 2018R1D1A1B07041091 National Research Foundation of Korea 2021S1A5A8062526
Corresponding Author	Haewon Byeon, DSc, PhD, Associate Professor, Director, Department of Medical Big Data, Inje University, 197 Inje-ro, Gimhae 50834, South Korea. bhwpuma@naver.com
Key Words	Dementia; Artificial intelligence; Clinical decision support system; Machine learning; Mild cognitive impairment
Core Tip	The predictive performance of machine learning techniques varies among studies because of the difference in machine data (especially, Y variables) imbalance, characteristics of features included in the model, and measurement methods of outcome variables. Therefore, further studies are continuously needed to check the predictive performance of each algorithm because, although some studies have proven that the performance of a specific machine learning algorithm is excellent, the results cannot be generalized for all types of data.
Citation	Byeon H. Screening dementia and predicting high dementia risk groups using machine learning. World J Psychiatr 2022; 12(2): 204-211

Received	2021-06-25 08:34
Peer-Review Started	2021-06-25 08:36
To Make the First Decision
Return for Revision	2021-09-05 21:12
Revised	2021-09-06 10:38
Second Decision	2022-01-17 05:42
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2022-01-20 05:22
Articles in Press	2022-01-20 05:22
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2022-02-09 08:11

ISSN	2220-3206 (online)
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