BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
3/28/2023 12:59:29 PM | Browse: 159 | Download: 434
Publication Name World Journal of Gastroenterology
Manuscript ID 81564
Country Romania
Received
2022-11-15 07:00
Peer-Review Started
2022-11-15 07:02
To Make the First Decision
Return for Revision
2022-12-11 22:26
Revised
2022-12-23 07:51
Second Decision
2023-03-15 03:13
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2023-03-16 17:04
Articles in Press
2023-03-16 17:04
Publication Fee Transferred
Edit the Manuscript by Language Editor
2023-03-08 03:33
Typeset the Manuscript
2023-03-20 09:01
Publish the Manuscript Online
2023-03-28 12:59
ISSN 1007-9327 (print) and 2219-2840 (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) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Radiology, Nuclear Medicine & Medical Imaging
Manuscript Type Minireviews
Article Title Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis
Manuscript Source Invited Manuscript
All Author List Alexandra Corina Faur, Daniela Cornelia Lazar and Laura Andreea Ghenciu
ORCID
Author(s) ORCID Number
Alexandra Corina Faur http://orcid.org/0000-0001-8953-5076
Daniela Cornelia Lazar http://orcid.org/0000-0002-6984-0046
Laura Andreea Ghenciu http://orcid.org/0000-0002-5326-5438
Funding Agency and Grant Number
Corresponding Author Alexandra Corina Faur, PhD, Additional Professor, Department of Anatomy and Embriology, “Victor Babeș” University of Medicine and Pharmacy Timișoara, Eftimie Murgu Sq. no. 2, Timișoara 300041, Timiș, Romania. faur.alexandra@umft.ro
Key Words Pancreatic cancer; Early pancreatic lesions; Pancreatic neoplasia; Artificial intelligence; Deep learning; Machine learning; Radiomics; Diagnosis; Pancreas
Core Tip To improve the clinical management and prognosis for patients with pancreatic cancer (PC), new diagnostic methods should be developed to identify precursor lesions. Artificial intelligence (AI) is a tool that can offer a personalized approach in this regard by analyzing a large quantity of heterogeneous data and can also help in decision-making, increasing the prediction accuracy for an early diagnosis. The aim of this study was to provide a comprehensive overview of the advances in detecting PC noninvasively with an emphasis on early lesions and AI.
Publish Date 2023-03-28 12:59
Citation Faur AC, Lazar DC, Ghenciu LA. Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis. World J Gastroenterol 2023; 29(12): 1811-1823
URL https://www.wjgnet.com/1007-9327/full/v29/i12/1811.htm
DOI https://dx.doi.org/10.3748/wjg.v29.i12.1811
Full Article (PDF) WJG-29-1811.pdf
Full Article (Word) WJG-29-1811.docx
Manuscript File 81564_Auto_Edited-LM.docx
Answering Reviewers 81564-Answering reviewers.pdf
Audio Core Tip 81564-Audio core tip.mp3
Conflict-of-Interest Disclosure Form 81564-Conflict-of-interest statement.pdf
Copyright License Agreement 81564-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate 81564-Language certificate.pdf
Peer-review Report 81564-Peer-review(s).pdf
Scientific Misconduct Check 81564-Bing-Wang JJ-2.png
Scientific Editor Work List 81564-Scientific editor work list.pdf