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.

The high-entropy ferroelectric fillers/polymer nanocomposites achieve ultra-high U_dis values of 8.7 J cm^-3 at 150 °C and 5.9 J cm^-3 at 200 °C, while maintaining an η of over 90%.

A new direct correlation between coordination geometry and catalytic performance is established through electronic modulation, offering a generalizable design principle for high-performance single-atom catalysts in CO₂ conversion.

This paper clarified the antecedents, attributes, consequences, and empirical referents of safe care that may contribute to safer care and help healthcare professionals ensure patient safety.