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Articles Published Processes
3/6/2025 10:23:11 AM | Browse: 34 | Download: 63
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Received |
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2024-08-22 08:49 |
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Peer-Review Started |
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2024-07-15 08:50 |
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To Make the First Decision |
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Return for Revision |
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2024-12-11 06:25 |
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Revised |
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2024-12-17 07:00 |
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Second Decision |
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2024-12-23 02:41 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2024-12-23 08:40 |
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Articles in Press |
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2024-12-23 08:40 |
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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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2024-12-30 04:41 |
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Publish the Manuscript Online |
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2025-03-06 10:23 |
| ISSN |
2222-0682 (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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2024. 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 |
Nursing |
| Manuscript Type |
Editorial |
| Article Title |
Innovative forecasting models for nurse demand in modern healthcare systems
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Kalpana Singh and Abdulqadir J Nashwan |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Abdulqadir J Nashwan, PhD, Department of Nursing and Midwifery Research, Hamad Medical Corporation, Rayyan Road, Doha 3050, Qatar. anashwan@hamad.qa |
| Key Words |
Nurse demand prediction; Time-series analysis; Machine learning; Simulation-based methods; Predictive models |
| Core Tip |
Accurate forecasting of nurse demand is critical for efficient workforce planning in healthcare. Leveraging advanced methods like time-series analysis, machine learning, and simulation models enables precise staffing predictions. These models address challenges posed by healthcare system complexities, seasonal fluctuations, and policy changes. By integrating these techniques, healthcare organizations can optimize resource allocation, reduce inefficiencies, and enhance patient care quality, ensuring adaptability in an evolving healthcare landscape. |
| Publish Date |
2025-03-06 10:23 |
| Citation |
<p>Singh K, Nashwan AJ. Innovative forecasting models for nurse demand in modern healthcare systems. <i>World J Methodol</i> 2025; 15(3): 99162</p> |
| URL |
https://www.wjgnet.com/2222-0682/full/v15/i3/99162.htm |
| DOI |
https://dx.doi.org/10.5662/wjm.v15.i3.99162 |
© 2004-2025 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
