Publication Name	Artificial Intelligence in Cancer
Manuscript ID	72357
Country	Brazil

Received	2021-10-12 21:52
Peer-Review Started	2021-10-12 21:53
To Make the First Decision
Return for Revision	2021-10-20 05:34
Revised	2021-10-22 21:07
Second Decision	2021-10-27 11:58
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2021-10-27 21:14
Articles in Press	2021-10-27 21:14
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2021-10-28 01:33
Publish the Manuscript Online	2021-10-28 08:03

ISSN	2644-3228 (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/
Copyright	© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
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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	Transplantation
Manuscript Type	Opinion Review
Article Title	Artificial neural network for prediction of acute kidney injury after liver transplantation for cirrhosis and hepatocellular carcinoma
Manuscript Source	Invited Manuscript
All Author List	Luis Cesar Bredt and Luis Alberto Batista Peres
ORCID	Author(s) ORCID Number Luis Cesar Bredt http://orcid.org/0000-0002-8487-1790 Luis Alberto Batista Peres http://orcid.org/0000-0001-5863-6720
Funding Agency and Grant Number
Corresponding Author	Luis Cesar Bredt, FRCS (Gen Surg), MD, PhD, Full Professor, Surgeon, Department of Surgical Oncology and General Surgery, University Hospital of Western Paraná, State University of Western Paraná, Tancredo Neves Avenue, Cascavel 85819-110, Paraná, Brazil. lcbredt@gmail.com
Key Words	Liver transplantation; Acute kidney injury; Artificial neural network; Prediction; Hepatocellular carcinoma; Postoperative
Core Tip	This opinion review aims to explore the potential benefits of artificial neural network models in predicting the occurrence of acute kidney injury in the postoperative period of liver transplantation for cirrhosis and hepatocellular carcinoma.
Publish Date	2021-10-28 08:03
Citation	Bredt LC, Peres LAB. Artificial neural network for prediction of acute kidney injury after liver transplantation for cirrhosis and hepatocellular carcinoma. Artif Intell Cancer 2021; 2(5): 51-59
URL	https://www.wjgnet.com/2644-3228/full/v2/i5/51.htm
DOI	https://dx.doi.org/10.35713/aic.v2.i5.51

Full Article (PDF)	AIC-2-51.pdf
Full Article (Word)	AIC-2-51.docx
Manuscript File	72357_Auto_Edited.docx
Answering Reviewers	72357-Answering reviewers.pdf
Audio Core Tip	72357-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	72357-Conflict-of-interest statement.pdf
Copyright License Agreement	72357-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	72357-Language certificate.pdf
Peer-review Report	72357-Peer-review(s).pdf
Scientific Editor Work List	72357-Scientific editor work list.pdf
CrossCheck Report	72357-CrossCheck report.pdf