Artificial intelligence in pancreatitis: A narrative review on advancing precision diagnosis, prognosis, and therapeutic strategies

Abstract

Pancreatitis poses persistent diagnostic and therapeutic challenges due to its heterogeneous clinical presentation, variable disease course, and lack of targeted interventions. Conventional tools, such as serum enzymes, cross-sectional imaging and clinical scoring systems, often exhibit limited sensitivity and prognostic value, especially during early or atypical stages. Moreover, therapeutic development remains slow, with limited progress toward personalized or mechanism-based strategies. These limitations highlight a critical need for integrative data-driven approaches. Artificial intelligence (AI) has emerged as a promising tool to enhance clinical decision-making in pancreatitis. This narrative review synthesizes recent progress in AI applications across three domains. First, AI-enabled diagnostic platforms incorporating radiomics, deep learning-based imaging analysis, and biomarker optimization have improved early detection and differentiation of pancreatic diseases. Second, AI-driven prognostic models now allow real-time severity prediction, complication forecasting, and recurrence risk assessment, some of which have been deployed in hospital information systems for intensive care units and mortality risk triage. Third, AI-assisted drug discovery and network pharmacology, particularly in combination with traditional Chinese medicine, have revealed novel therapeutic opportunities. Despite encouraging developments, challenges remain in data standardization, model transparency and clinical validation. A multidisciplinary strategy integrating omics data, longitudinal monitoring and pharmacological modeling may help bridge current gaps and advance precision medicine in pancreatitis care.

Keywords: Pancreatitis; Artificial intelligence; Machine learning; Deep learning; Diagnosis; Prognosis management; Therapeutics; Network pharmacology; Traditional Chinese medicine

Core Tip: This narrative review summarizes recent advances in artificial intelligence (AI) applications for pancreatitis. It covers AI-enhanced diagnosis through imaging and biomarker analysis, real-time prognostication using machine learning models, and AI-assisted therapeutic innovation, including integration with network pharmacology and traditional Chinese medicine. The review also highlights clinically implemented models and discusses current limitations and future directions for AI deployment in pancreatitis care.