Enhancing medical evidence discovery through Interactive Pattern Recognition and Process Mining

Abstract

Surrounded by heterogeneous clinical data, medical staff needs to take easily the right decisions at the point of care in real time supported by medical evidence. Up to few years ago, evidence was not available at the point of care, making use of doctor's experience or heavy books. Nowadays, the challenge is to have such decision support systems available at any time, any place and any device. Interactive Pattern Recognition is a good approach to infer knowledge based on previous existing datasets whereas process mining is the tool to handle such knowledge in a very pragmatic way, helping medical staff to visualize the whole healthcare case.