BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
3/28/2023 12:59:29 PM | Browse: 518 | Download: 1551
 |
Received |
|
2022-11-15 07:00 |
|
Peer-Review Started |
|
2022-11-15 07:02 |
|
First Decision by Editorial Office Director |
|
2022-12-11 22:26 |
|
Return for Revision |
|
2022-12-11 22:26 |
|
Revised |
|
2022-12-23 07:51 |
 |
Publication Fee Transferred |
|
|
|
Second Decision by Editor |
|
2023-03-15 03:13 |
|
Second Decision by Editor-in-Chief |
|
|
|
Final Decision by Editorial Office Director |
|
2023-03-16 17:04 |
|
Articles in Press |
|
2023-03-16 17:04 |
|
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 |
|
| 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 |
All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.
