Predicting and Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence in Pancreatic Cancer

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Abstract
Pancreatic cancer remains one of the most lethal cancers, primarily due to its late diagnosis and limited treatment options. This review examines the challenges and potential of using immunotherapy to treat pancreatic cancer, highlighting the role of artificial intelligence (AI) as a promising tool to enhance early detection and monitor the effectiveness of these therapies. By synthesizing recent advancements and identifying gaps in the current research, this review aims to provide a comprehensive overview of how AI and immunotherapy can be integrated to develop more personalized and effective treatment strategies. The insights from this review may guide future research efforts and contribute to improving patient outcomes in pancreatic cancer management.
Funding Information
  • the National Cancer Institute of the National Institutes of Health (R01CA209886, R01CA241532, P30CA062203)
  • University of California Irvine Anti-Cancer Challenge Pilot (R01CA209886, R01CA241532, P30CA062203)
  • Society of Interventional Radiology Pilot Research (R01CA209886, R01CA241532, P30CA062203)

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