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World J Gastroenterol. Mar 28, 2023; 29(12): 1811-1823
Published online Mar 28, 2023. doi: 10.3748/wjg.v29.i12.1811
Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis
Alexandra Corina Faur, Daniela Cornelia Lazar, Laura Andreea Ghenciu
Alexandra Corina Faur, Department of Anatomy and Embriology, “Victor Babeș” University of Medicine and Pharmacy Timișoara, Timișoara 300041, Timiș, Romania
Daniela Cornelia Lazar, Department V of Internal Medicine I, Discipline of Internal Medicine IV, University of Medicine and Pharmacy “Victor Babes” Timișoara, Timișoara 300041, Timiș, Romania
Laura Andreea Ghenciu, Department III, Discipline of Pathophysiology, “Victor Babeș” University of Medicine and Pharmacy, Timișoara 300041, Timiș, Romania
Author contributions: Faur AC and Lazar DC contributed to manuscript drafting and writing; Faur AC, Lazar DC, and Ghenciu LA were involved in literature search; Faur AC and Ghenciu LA participated in study conceptualization and design; Faur AC and Lazar DC supervised the manuscript; and all authors have read and agreed to the final version of the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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/
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
Received: November 15, 2022
Peer-review started: November 15, 2022
First decision: December 11, 2022
Revised: December 23, 2022
Accepted: March 15, 2023
Article in press: March 15, 2023
Published online: March 28, 2023
Processing time: 133 Days and 6 Hours
Core Tip

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.