From Bits to Bedside: From Data to Knowledge in Vascular Surgery

The Data–Information–Knowledge (DIK) hierarchy describes how clinical observations are progressively transformed into actionable knowledge. Although digital technologies are beginning to reshape vascular surgery, their impact is often discussed in isolation rather than as components of a continuous knowledge-generation process. This narrative review applies the DIK framework to examine how recent technological advances are transforming each stage of knowledge generation in vascular surgery. Emphasis was placed on data modeling, computer vision and natural language processing, as well as retrieval-augmented generation (RAG)-based large language model applications. Despite these advances, limitations remain, including data quality, external validation, generalizability, and the reliability and transparency of generated recommendations. Maximizing future knowledge generation requires coordinated advances across all three layers, especially on the data layer.