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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72420, first published .
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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

Journals

  1. Almufareh M, Tehsin S, Humayun M, Kausar S, Farooq A, Aldossary H, Aljohani A. From radiomics to transformers in pancreatic cancer detection and prognosis. Frontiers in Medicine 2026;12 View
  2. Cong F, Tian K, Gao Q, Wang F, Sun P, Xu N. CT Radiomics–Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study. JMIR Medical Informatics 2026;14:e77349 View
  3. Wang Z, Qu W, Cai W, Wang C, Lyu C, Xie Q, Chu Q, Shen Y, Xiao P, Li F, Zhang Q, Li J, Lee J, Li Z. PancDS in Real‐World Practice: A Prospective Multicenter Validation of a Clinical Decision‐Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis. Advanced Science 2026 View
  4. Quan S, Li G, Liu S, Wu J, He P, Hu J. Clinicopathological features of pancreatic solid pseudopapillary neoplasm: A retrospective single-center study of 32 cases in Guangzhou, China. Pathology - Research and Practice 2026;286:156582 View
  5. Virk M, Rajamohan N, Kodali G, Khatri G, Kaza R. Pancreatic malignancy in disguise: imaging pitfalls and mimickers of pancreatic ductal adenocarcinoma. Abdominal Radiology 2026 View