Treating cancer patients through predictive monitoring of business processes

Mar 15, 2018 · Utrecht, Netherlands

Predictive monitoring of business processes - how data analytics can support treatment of cancer patients We are excited to invite you to our bi-monthly Meetup! Our guest speaker is Thomas Hildebrandt, Head of Process Intelligence, Modelling and Optimisation Research Group at the IT University of Copenhagen and BPM Consultant.

Schedule:
• Doors open at 18:00; food will be provided
• Talk starts at 19:00
• Drinks as of 20:00

Thomas will present new work on predictive monitoring of business processes. Modern information systems that support complex business processes generally maintain significant amounts of process execution data. These historic execution data can be analyzed in order to predictively monitor correct business process execution. The approach uses linear temporal logic to define constraints on business process execution and predict violations of these constraints. As a result more efficient and consistent case management can be achieved; something we can all benefit from as citizens, patients, customers etc.

Thomas Hildebrandt is professor in Software Engineering at the Department of Computer Science Copenhagen University after he was the Head of Process Intelligence, Modelling and Optimisation Research Group at the IT University of Copenhagen and a BPM Consultant. He obtained his PhD in Computer Science in 1999 at Aarhus University and has since then been employed at IT University of Copenhagen. His research focuses on models of concurrent and mobile processes for reliable and secure process execution and composition in complex it-systems.

Event organizers
  • Real Data Science Meetup

    This group has a focus on real data science. How is this changing the way we work, play, live? What are the underlying principles, methods, algoritms and maths that have changed the way we see the world? Rather than Vendor Marketing and Big Words, we would like to focus on what is real; get a spade deeper and truly understand data science. Let's bring the science back into data science...

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