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

Foundations of AI (53)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40702, first published .
Deep Learning to Detect Pancreatic Cystic Lesions on Abdominal Computed Tomography Scans: Development and Validation Study

Deep Learning to Detect Pancreatic Cystic Lesions on Abdominal Computed Tomography Scans: Development and Validation Study

Deep Learning to Detect Pancreatic Cystic Lesions on Abdominal Computed Tomography Scans: Development and Validation Study

Authors of this article:

Maria Montserrat Duh1 Author Orcid Image ;   Neus Torra-Ferrer1 Author Orcid Image ;   Meritxell Riera-Marín2 Author Orcid Image ;   Dídac Cumelles2 Author Orcid Image ;   Júlia Rodríguez-Comas2 Author Orcid Image ;   Javier García López2 Author Orcid Image ;   Mª Teresa Fernández Planas1 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

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  1. Berbís M, Godino F, Rodríguez-Comas J, Nava E, García-Figueiras R, Baleato-González S, Luna A. Radiomics in CT and MR imaging of the liver and pancreas: tools with potential for clinical application. Abdominal Radiology 2023;49(1):322 View
  2. Wang S, Hu Z, Li C, He X, Zhu C, Wang Y, Sattar U, Bazojoo V, He H, Blumenfeld J, Prince M. Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning. Tomography 2024;10(7):1148 View
  3. Torra-Ferrer N, Duh M, Grau-Ortega Q, Cañadas-Gómez D, Moreno-Vedia J, Riera-Marín M, Aliaga-Lavrijsen M, Serra-Prat M, García López J, González-Ballester M, Fernández-Planas M, Rodríguez-Comas J. Machine Learning-Driven Radiomics Analysis for Distinguishing Mucinous and Non-Mucinous Pancreatic Cystic Lesions: A Multicentric Study. Journal of Imaging 2025;11(3):68 View
  4. Yang L, Zhang X, Li Z, Wang J, Zhang Y, Shan L, Shi X, Si Y, Wang S, Li L, Wu P, Xu N, Liu L, Yang J, Leng J, Yang M, Zhang Z, Wang J, Dong X, Yang G, Yan R, Li W, Liu Z, Li W. Localization and Classification of Adrenal Masses in Multiphase Computed Tomography: Retrospective Study. Journal of Medical Internet Research 2025;27:e65937 View
  5. Moglia A, Cavicchioli M, Mainardi L, Cerveri P. Deep learning for pancreas segmentation on computed tomography: a systematic review. Artificial Intelligence Review 2025;58(8) View