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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

Kaile Chen
Kaile Chen

Project Team 

Fernando Seoane Martinez
Fernando Seoane Martinez
Farhad Abtahi
Farhad Abtahi forskare

Hong Xu

Juan-Jesus Carrero

Carlos Fernández Llatas