Publication Name	World Journal of Gastroenterology
Manuscript ID	90485
Country	China

Received	2023-12-05 13:46
Peer-Review Started	2023-12-05 13:46
To Make the First Decision
Return for Revision	2024-01-04 09:44
Revised	2024-01-15 10:57
Second Decision	2024-02-25 02:38
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2024-02-25 04:41
Articles in Press	2024-02-25 04:41
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-03-04 09:28
Publish the Manuscript Online	2024-03-14 17:31

ISSN	1007-9327 (print) and 2219-2840 (online)
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Category	Gastroenterology & Hepatology
Manuscript Type	Review
Article Title	Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives
Manuscript Source	Invited Manuscript
All Author List	Feng Yang, John A Windsor and De-Liang Fu
ORCID	Author(s) ORCID Number Feng Yang http://orcid.org/0000-0001-8790-6072 John A Windsor http://orcid.org/0000-0001-5995-5432 De-Liang Fu http://orcid.org/0000-0003-4060-8101
Funding Agency and Grant Number
Corresponding Author	Feng Yang, MD, PhD, Doctor, Surgeon, Department of Pancreatic Surgery, Pancreatic Disease Institute, Huashan Hospital, Fudan University, 12 Central Urumqi Road, Shanghai 200040, China. yffudan98@126.com
Key Words	Pancreatic fistula; Pancreaticoduodenectomy; Distal pancreatectomy; Central pancreatectomy; Prediction model; Machine learning; Artificial intelligence
Core Tip	Postoperative pancreatic fistula (POPF) is a common complication following pancreatectomy, associated with increased morbidity and mortality. Optimizing prediction models for POPF is a critical focus in surgical research. Although over sixty models following pancreaticoduodenectomy have been documented, their predictive accuracy remains suboptimal across diverse populations. The validation of models after distal pancreatectomy is anticipated, while POPF prediction after central pancreatectomy requires further development and validation. Machine learning and big data analytics offer promising prospects for enhancing prediction model accuracy. Personalized prediction models and novel imaging technologies, such as AI-based radiomics, may further refine predictive models.
Publish Date	2024-03-14 17:31
Citation	Yang F, Windsor JA, Fu DL. Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives. World J Gastroenterol 2024; 30(10): 1329-1345
URL	https://www.wjgnet.com/1007-9327/full/v30/i10/1329.htm
DOI	https://dx.doi.org/10.3748/wjg.v30.i10.1329

Full Article (PDF)	WJG-30-1329-with-cover.pdf
Full Article (Word)	WJG-30-1329.docx
Manuscript File	90485_Auto_Edited-YJP.docx
Answering Reviewers	90485-Answering reviewers.pdf
Audio Core Tip	90485-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	90485-Conflict-of-interest statement.pdf
Copyright License Agreement	90485-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	90485-Language certificate.pdf
Peer-review Report	90485-Peer-review(s).pdf
Scientific Misconduct Check	90485-Bing-Yan JP-2.png
Scientific Editor Work List	90485-Scientific editor work list.pdf