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REVIEW

Clinical Application Progress of Artificial Intelligence in Pancreatic Cancer: From Diagnosis to Immunotherapy

Zehao Wei1,#, Xuejian Liu2,#, Zheng Zhang1, Yimin Ma2,*, Min Xu1,*
1 Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China
2 Department of Radiology, Xinjiang 474 Hospital, Urumqi, China
* Corresponding Author: Yimin Ma. Email: email; Min Xu. Email: email
# These authors contributed equally to this work

Oncology Research https://doi.org/10.32604/or.2026.078793

Received 08 January 2026; Accepted 12 March 2026; Published online 09 April 2026

Abstract

Pancreatic cancer is one of the most lethal malignancies, characterized by difficulties in early diagnosis, limited therapeutic options, and generally poor patient prognosis. In recent years, immunotherapy has provided new opportunities for the treatment of pancreatic cancer; however, its clinical efficacy has been substantially constrained by the complex tumor microenvironment (TME) and immune evasion mechanisms. With the rapid advancement of artificial intelligence (AI) technologies, AI has demonstrated great potential in the early detection of pancreatic cancer, prediction of immunotherapeutic responses, and design of personalized treatment strategies. This review systematically summarizes the latest advances in the application of artificial intelligence in pancreatic cancer immunotherapy, with a particular focus on key AI assisted technologies, including tumor immune microenvironment characterization, prediction of genetic mutation profiles, nanomedicine design, and dynamic monitoring of therapeutic responses. By integrating single cell sequencing and multi-omics data analyses, we discuss how AI can effectively address critical bottlenecks in immunotherapy. In addition, this article analyzes current technical challenges and future development trends, aiming to provide a theoretical foundation and practical guidance for achieving precision immunotherapy in pancreatic cancer and to promote clinical translation and application in this field.

Keywords

Pancreatic cancer; artificial intelligence (AI); immunotherapy; tumor microenvironment (TME)

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