On the Application of Interactive Process Mining to Clinical Epidemiology Studies with Real World Data
Nowadays, with longer life expectancy there is an increased need for managing chronic conditions, and this is becoming unsustainable for public healthcare.
Also, with the advent of the era of big data, the healthcare information system could be more complex. So, there is a need to find a methodology that could account for the complexity and ease the burden of public healthcare.
The main objective of our research is to demonstrate how real-world data and biomedical knowledge can be integrated in a synergistic way, creating an interactive methodology for information mining and hypothesis generation.
Project leader
Project team
Hong Xu
Juan-Jesus Carrero
Carlos Fernández Llatas