从数据治理到智能应用:医学"干实验室"建设的实践与思考OA

This study aims to develop a medical"dry laboratory"model that treats healthcare data as the primary research subject and employs computational science and AI as core methodologies.Based on the practice of a large tertiary hospital,we present a construction framework featuring a full-cycle model spanning data cultivation,governance,value extraction,and ecological feedback—transforming medical data from a static resource into a living asset.Innovatively,the"dry laboratory"was integrated into the residency training rotation to systematically cultivate data literacy.Practice has shown that the framework establishes the"dry laboratory"as a digital research entity,creating a closed-loop system that integrates clinical practice with data analytics,significantly enhancing the usability of multimodal data and enabling scalable training in data competence.In conclusion,the medical"dry laboratory"represents a new digital research paradigm distinct from traditional wet laboratories.Its implementation provides a reference framework and introduces an integrated"dry-wet"research model combining wet-lab experiments with data cultivation,demonstrating significant value for enhancing medical innovation,cultivating interdisciplinary talent,and advancing smart healthcare.