Building an Artificial Intelligence Laboratory Based on Real World Data: The Experience of Gemelli Generator

The problem of transforming Real World Data into Real World Evidence is becoming increasingly important in the frameworks of Digital Health and Personalized Medicine, especially with the availability of modern algorithms of Artificial Intelligence high computing power, and large storage facilities. Even where Real World Data are well maintained in a hospital data warehouse and are made available for research purposes, many aspects need to be addressed to build an effective architecture enabling researchers to extract knowledge from data.

The huge availability of data from different generic and special purpose information technology (IT) systems in today’s healthcare process is profoundly impacting knowledge management for medical specialists, by providing new insight and understanding in all diagnostic and prognostic domains. This will progressively help reshaping the care process to design personalized therapies and improve quality of care.

By leveraging the continuous flow of data produced during routine clinical practice–what is now generically defined as the generation of Real World Evidence - researchers and medical staff have at reach new and better ways to take decisions.