Publication Name	World Journal of Gastroenterology
Manuscript ID	81564
Country	Romania

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
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.
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

Received	2022-11-15 07:00
Peer-Review Started	2022-11-15 07:02
To Make the First Decision
Return for Revision	2022-12-11 22:26
Revised	2022-12-23 07:51
Second Decision	2023-03-15 03:13
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2023-03-16 17:04
Articles in Press	2023-03-16 17:04
Publication Fee Transferred
Edit the Manuscript by Language Editor	2023-03-08 03:33
Typeset the Manuscript	2023-03-20 09:01

ISSN	1007-9327 (print) and 2219-2840 (online)
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