Publication Name	World Journal of Gastrointestinal Surgery
Manuscript ID	96526
Country	Italy

Received	2024-05-08 23:03
Peer-Review Started	2024-05-08 23:03
To Make the First Decision
Return for Revision	2024-06-19 06:14
Revised	2024-06-28 10:21
Second Decision	2024-07-09 02:42
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-07-09 06:33
Articles in Press	2024-07-09 06:33
Publication Fee Transferred
Edit the Manuscript by Language Editor	2024-07-10 14:54
Typeset the Manuscript	2024-07-17 00:28
Publish the Manuscript Online	2024-09-28 04:34

ISSN	1948-9366 (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/
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Category	Surgery
Manuscript Type	Editorial
Article Title	Advancing perioperative optimization in Crohn's disease surgery with machine learning predictions
Manuscript Source	Invited Manuscript
All Author List	Olga Maria Nardone, Fabiana Castiglione and Simone Maurea
ORCID	Author(s) ORCID Number Olga Maria Nardone http://orcid.org/0000-0002-9554-4785
Funding Agency and Grant Number
Corresponding Author	Olga Maria Nardone, MD, PhD, Assistant Professor, Department of Public Health, University of Naples Federico II, Via Pansini 5, Naples 80131, Italy. olgamaria.nardone@unina.it
Key Words	Crohn's disease; Surgery; Postoperative complications; Ileocecal resection; Machine learning
Core Tip	Preoperative optimization for patients with Crohn's disease presents numerous challenges. Traditional research methods are insufficient to address the expanding array of questions in this field. Hence, there is a growing need to explore and develop new tools grounded in advanced technologies, such as computer simulation models and artificial intelligence. Employing machine learning approaches can significantly enhance patient risk stratification and the formulation of preoperative optimization strategies, ultimately aiming to improve post-surgical outcomes.
Publish Date	2024-09-28 04:34
Citation	<p>Nardone OM, Castiglione F, Maurea S. Advancing perioperative optimization in Crohn's disease surgery with machine learning predictions. <i>World J Gastrointest Surg</i> 2024; 16(10): 3091-3093</p>
URL	https://www.wjgnet.com/1948-9366/full/v16/i10/3091.htm
DOI	https://dx.doi.org/10.4240/wjgs.v16.i10.3091

Full Article (PDF)	WJGS-16-3091-with-cover.pdf
Manuscript File	96526_Auto_Edited_071636.docx
Answering Reviewers	96526-answering-reviewers.pdf
Audio Core Tip	96526-audio.m4a
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Non-Native Speakers of English Editing Certificate	96526-non-native-speakers.pdf
Peer-review Report	96526-peer-reviews.pdf
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Scientific Editor Work List	96526-scientific-editor-work-list.pdf
CrossCheck Report	96526-crosscheck-report.pdf