This paper is in the following e-collection/theme issue:

Digital Health Reviews (1727) Gastroenterology and Hepatology (129) Medical imaging (111) Cancer Prognosis Models and Machine Learning (67) Computer-Aided Diagnosis (252) Decision Support for Health Professionals (1542) Machine Learning (2077) Artificial Intelligence (2135) Digital Health Reviews (1727)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72420, first published .
Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis

Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis

Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis

Authors of this article:

Lechang Zhang1 Author Orcid Image ;   Dewei Li2 Author Orcid Image ;   Tong Su1 Author Orcid Image ;   Tong Xiao1 Author Orcid Image ;   Shulei Zhao1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Lechang Zhang   1 , MM ;   Dewei Li   2 , MM ;   Tong Su   1 , MM ;   Tong Xiao   1 , MM ;   Shulei Zhao   1 , MD

1 Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China

2 Department of Infectious Diseases, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China

Corresponding Author:

  • Shulei Zhao, MD
  • Department of Gastroenterology
  • Shandong Provincial Hospital Affiliated to Shandong First Medical University
  • 324 Jingwu Weiqi Rd
  • Jinan 250021
  • China
  • Phone: 86 13853121769
  • Email: wenzhu24@126.com