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Articles Published Processes
2/9/2022 6:44:54 AM | Browse: 327 | Download: 1051
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Received |
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2021-08-23 11:30 |
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Peer-Review Started |
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2021-08-23 11:32 |
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To Make the First Decision |
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Return for Revision |
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2021-12-04 22:18 |
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Revised |
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2021-12-10 16:30 |
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Second Decision |
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2022-01-06 03:31 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2022-01-06 18:54 |
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Articles in Press |
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2022-01-06 18:54 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2022-02-07 07:01 |
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Publish the Manuscript Online |
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2022-02-09 06:44 |
ISSN |
1948-9358 (online) |
Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
Copyright |
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. |
Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Neuroimaging |
Manuscript Type |
Retrospective Study |
Article Title |
Large-scale functional connectivity predicts cognitive impairment related to type 2 diabetes mellitus
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Manuscript Source |
Unsolicited Manuscript |
All Author List |
An-Ping Shi, Ying Yu, Bo Hu, Yu-Ting Li, Wen Wang and Guang-Bin Cui |
ORCID |
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Funding Agency and Grant Number |
Funding Agency |
Grant Number |
National Natural Science Foundation of China |
81771815 |
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Corresponding Author |
Guang-Bin Cui, BMed, Doctor, PhD, Academic Research, Chief Doctor, Chief Physician, Professor, Research Dean, Department of Radiology, the Affiliated Tangdu Hospital of Air Force Medical University, 569 Xinsi Road, Xi'an 710038, Shaanxi Province, China. cuigbtd@163.com |
Key Words |
Connectome-based predictive modeling; Large-scale functional connectivity; Mild cognitive impairment; Resting-state functional magnetic resonance; Support vector machine; Type 2 diabetes mellitus |
Core Tip |
Large-scale functional connectivity (LSFC) patterns show unique characteristics. Abnormal LSFC patterns have been observed in patients with dementia or mild cognitive impairment. Patients with diabetes may develop mild cognitive impairment that could potentially progress to dementia. We assessed the applicability of LSFC-related discriminative features to predict the cognitive level of patients with type 2 diabetes mellitus using a connectome-based predictive modeling and support vector machine. We found that the application of these two techniques, based on LSFC patterns, to predict neurocognitive abilities, can complement conventional neurocognitive assessments and aid the management of type 2 diabetes mellitus. |
Publish Date |
2022-02-09 06:44 |
Citation |
Shi AP, Yu Y, Hu B, Li YT, Wang W, Cui GB. Large-scale functional connectivity predicts cognitive impairment related to type 2 diabetes mellitus. World J Diabetes 2022; 13(2): 110-125 |
URL |
https://www.wjgnet.com/1948-9358/full/v13/i2/110.htm |
DOI |
https://dx.doi.org/10.4239/wjd.v13.i2.110 |
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