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Articles Published Processes
12/19/2022 3:35:01 AM | Browse: 173 | Download: 338
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Received |
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2022-08-01 14:00 |
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Peer-Review Started |
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2022-08-01 14:03 |
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To Make the First Decision |
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Return for Revision |
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2022-11-11 09:37 |
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Revised |
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2022-11-17 03:04 |
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Second Decision |
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2022-12-08 03:22 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2022-12-08 23:11 |
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Articles in Press |
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2022-12-08 23:11 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2022-12-03 07:23 |
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Typeset the Manuscript |
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2022-12-14 08:37 |
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Publish the Manuscript Online |
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2022-12-19 03:35 |
| ISSN |
2218-4333 (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 |
Obstetrics & Gynecology |
| Manuscript Type |
Retrospective Cohort Study |
| Article Title |
Machine learning-assisted ensemble analysis for the prediction of urinary tract infection in elderly patients with ovarian cancer after cytoreductive surgery
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Jiao Ai, Yao Hu, Fang-Fang Zhou, Yi-Xiang Liao and Tao Yang |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Tao Yang, MD, Surgical Oncologist, Department of Urology, Jingzhou Central Hospital, Jingzhou Hospital Affiliated to Yangtze University, No. 26 Chuyuan Road, Jingzhou 434020, Hubei Province, China. yangtaotao123321@163.com |
| Key Words |
Cytoreductive surgery; Machine learning; Ovarian cancer; Risk factors; Urinary tract infection |
| Core Tip |
Using a machine learning-based algorithm, we developed a feasible and robust method to identify factors that are significant for predicting urinary tract infections. The random forest classifier was especially robust and can improve the prediction and early detection of urinary tract infections in patients with ovarian cancer. In addition, the five most crucial factors were age, body mass index, catheter, catheter intubation times, blood loss, diabetes and hypoproteinaemia. Clinicians may find it extremely helpful to assess the individualised risk of urinary tract infections in clinical practice by incorporating the presentation of simple clinical data. |
| Publish Date |
2022-12-19 03:35 |
| Citation |
Ai J, Hu Y, Zhou FF, Liao YX, Yang T. Machine learning-assisted ensemble analysis for the prediction of urinary tract infection in elderly patients with ovarian cancer after cytoreductive surgery. World J Clin Oncol 2022; 13(12): 967-979 |
| URL |
https://www.wjgnet.com/2218-4333/full/v13/i12/967.htm |
| DOI |
https://dx.doi.org/10.5306/wjco.v13.i12.967 |
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