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Langan et al. Art Int Surg 2023;3:140-6                                         Artificial
               DOI: 10.20517/ais.2023.13
                                                                               Intelligence Surgery




               Editorial                                                                     Open Access



               Role of artificial intelligence in pancreatic cystic
               neoplasms: modernizing the identification and

               longitudinal management of pancreatic cysts


               Russell C. Langan 1,2,3 , Henry A. Pitt 1,2,3 , Erika Schneider 4
               1
                Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 07039, USA.
               2
                Rutgers Robert Wood Johnson University Medical School, New Brunswick, NJ 07039, USA.
               3
                Department of Surgery, Cooperman Barnabas Medical Center, RWJ Barnabas Health, New Brunswick, NJ 07039, USA.
               4
                EON Health, Denver, CO 80246, USA.
               Correspondence to: Prof. Russell C. Langan, Division of Surgical Oncology, Rutgers Cancer Institute of New Jersey, 94 Old Short
               Hills Road, Suite 1172, Livingston, NJ 07039, USA. E-mail: Russell.Langan@rwjbh.org
               How to cite this article: Langan RC, Pitt HA, Schneider E. Role of artificial intelligence in pancreatic cystic neoplasms:
               modernizing the identification and longitudinal management of pancreatic cysts. Art Int Surg 2023;3:140-6.
               https://dx.doi.org/10.20517/ais.2023.13

               Received: 11 Apr 2023  First Decision: 17 May 2023  Accepted: 21 Jun 2023  Published: 3 Jul 2023

               Academic Editor: Andrew A. Gumbs  Copy Editor: Dan Zhang  Production Editor: Dan Zhang

               Abstract
               Mucinous cysts of the pancreas represent the most common identifiable precursor to pancreatic cancer. Evidence-
               based guidelines for screening and surveillance exist, but many patients are either not properly identified or lost to
               follow-up. Artificial Intelligence, specifically computational linguistics models, can dramatically improve patient
               identification and mitigate risk through modernizing pancreatic cyst longitudinal surveillance. Herein we discuss
               the risk associated with mucinous cysts of the pancreas and modern approaches to patient identification and
               follow-up.

               Keywords: Pancreatic cyst, mucinous cysts, intraductal papillary mucinous cystic neoplasm (IPMN), mucinous
               cystic neoplasm (MCN), pancreatic duct adenocarcinoma, computational linguistics



               INTRODUCTION
               Mucinous cysts of the pancreas represent the most common identifiable precursor to pancreatic cancer. In
               2021, pancreas cancer represented the tenth and eighth most commonly diagnosed cancer in men and






                           © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0
                           International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
                           adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
               long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
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