[Computational medicine empowers multi-dimensional diagnosis and treatment of pancreatic cancer]

Due to its high genomic heterogeneity and dense desmoplastic microenvironment, traditional diagnosis and treatment for pancreatic ductal adenocarcinoma (PDAC) have limited effects. The management of PDAC is further complicated by persistent clinical bottlenecks,including inadequate accuracy in image-based staging, high surgical complexity,and limited systemic treatment options prone to drug resistance. These problems urgently require breakthroughs to enhance PDAC treatment outcomes and long-term survival. In recent years, computational medicine,which integrates artificial intelligence, machine learning, high-throughput multi-omics, and mathematical modeling, has sought to overcome these formidable challenges. It is currently driving a paradigm shift in the comprehensive diagnosis and treatment of PDAC,moving from a population-based standardized clinical protocols toward a novel framework characterized by digitalization,intelligence,multi-dimensionality,and precision. This article summarizes the cutting-edge advancements of computational medicine in the multi-dimensional diagnosis and treatment of PDAC,focusing on three key areas: radiological evaluation,surgical assistance,and pharmacotherapy. Although numerous challenges remain, the exponential growth in computational efficiency,which is coupled with the continuous maturation of explainable artificial intelligence,positions computational medicine to play a pivotal role in the global effort to conquer PDAC.