Health AI Central
Peer-Reviewed Publication
Gut2026April 28, 2026Journal Article

Next-generation AI for visually occult pancreatic cancer detection in a low-prevalence setting with longitudinal stability and multi-institutional generalisability.

Sovanlal Mukherjee1, Ajith Antony1,2, Nandakumar G Patnam1,3, Kamaxi H Trivedi1,3, Aashna Karbhari1,3, Khurram Khaliq Bhinder1, Armin Zarrintan1, Joel G Fletcher1, Mark Truty4, Matthew P Johnson5, Suresh T Chari6, Ajit Harishkumar Goenka7
1Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
2Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
3Radiology, University of Washington, Seattle, Washington, USA.
4Surgery, Mayo Clinic, Rochester, Minnesota, USA.
5Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
6Gastroenterology, Hepatology and Nutrition, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
7Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA goenka.ajit@mayo.edu.
PubMed PMC DOI PDF

Abstract

BACKGROUND: Failure of conventional imaging to detect pancreatic ductal adenocarcinoma (PDA) at its visually occult pre-diagnostic stage is a primary barrier to improving its otherwise poor rate of survival. OBJECTIVE: To develop and validate the Radiomics-based Early Detection MODel (REDMOD), an AI framework to identify subvisual radiomic signatures of pre-diagnostic PDA on standard-of-care CT.…

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