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Articles Published Processes
3/28/2023 12:59:29 PM | Browse: 298 | Download: 859
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Received |
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2022-11-15 07:00 |
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Peer-Review Started |
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2022-11-15 07:02 |
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To Make the First Decision |
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Return for Revision |
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2022-12-11 22:26 |
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Revised |
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2022-12-23 07:51 |
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Second Decision |
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2023-03-15 03:13 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2023-03-16 17:04 |
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Articles in Press |
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2023-03-16 17:04 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2023-03-08 03:33 |
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Typeset the Manuscript |
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2023-03-20 09:01 |
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Publish the Manuscript Online |
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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
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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 |
Radiology, Nuclear Medicine & Medical Imaging |
| Manuscript Type |
Minireviews |
| Article Title |
Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Alexandra Corina Faur, Daniela Cornelia Lazar and Laura Andreea Ghenciu |
| ORCID |
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| Funding Agency and Grant Number |
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| 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 |
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