Abstract

Mucinous cysts of the pancreas represent the most common identifiable precursor to pancreatic cancer. Evidence-based guidelines for screening and surveillance exist, but many patients are either not properly identified or lost to follow-up. Artificial Intelligence, specifically computational linguistics models, can dramatically improve patient identification and mitigate risk through modernizing pancreatic cyst longitudinal surveillance. Herein we discuss the risk associated with mucinous cysts of the pancreas and modern approaches to patient identification and follow-up.

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