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Articles Published Processes
10/9/2023 11:18:42 AM | Browse: 194 | Download: 654
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Received |
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2023-08-01 00:41 |
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Peer-Review Started |
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2023-08-01 00:42 |
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To Make the First Decision |
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Return for Revision |
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2023-08-16 01:59 |
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Revised |
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2023-08-21 01:57 |
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Second Decision |
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2023-09-07 06:06 |
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Accepted by Journal Editor-in-Chief |
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2023-09-09 13:25 |
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Accepted by Executive Editor-in-Chief |
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2023-09-14 08:22 |
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Articles in Press |
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2023-09-14 08:22 |
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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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2023-09-28 04:16 |
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Publish the Manuscript Online |
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2023-10-09 11:18 |
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) 2023. 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 |
Endocrinology & Metabolism |
Manuscript Type |
Retrospective Study |
Article Title |
Establishment and evaluation of a risk prediction model for gestational diabetes mellitus
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Manuscript Source |
Unsolicited Manuscript |
All Author List |
Qing Lin and Zhuan-Ji Fang |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Zhuan-Ji Fang, MM, Associate Chief Physician, Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, No. 18 Daoshan Rd., Gulou Dist, Fuzhou 350001, Fujian Province, China. fzlqtg@163.com |
Key Words |
Gestational diabetes mellitus; Prediction model; Model evaluation; Random forest model; Nomograms; Risk factor |
Core Tip |
Gestational diabetes mellitus (GDM) is a common pregnancy complication, which has an important impact on maternal and child health. Early prediction of GDM can result in timely interventions in patients and improve pregnancy outcomes. This study examined various risk factors associated with GDM and established and compared two prediction models: The nomogram model and the random forest model. The random forest model has good predictive ability, which can effectively predict the risk of GDM and provide accurate references for early prevention and management of GDM. |
Publish Date |
2023-10-09 11:18 |
Citation |
Lin Q, Fang ZJ. Establishment and evaluation of a risk prediction model for gestational diabetes mellitus. World J Diabetes 2023; 14(10): 1541-1550 |
URL |
https://www.wjgnet.com/1948-9358/full/v14/i10/1541.htm |
DOI |
https://dx.doi.org/10.4239/wjd.v14.i10.1541 |
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