Big data for better care
Big data science is playing an increasingly significant role in medicine. For instance, Professor Andre Dekker and his team are building a global medical data infrastructure and using ‘machine learning’ to mine it for new information. This has already resulted in algorithms that predict the outcome of administering specific treatments to specific patients.
Though the process is not straightforward, given the privacy issues, difficulty of combining information that may be structured in different ways and the many languages involved, the results are well worth it. By harnessing artificial intelligence, the medical world will be able to characterise tumours with more precision and more accurately predict chances of survival, thus enabling doctors and patients to make better treatment decisions (lecture in Dutch).
About the speaker
Professor Andre Dekker is a board-certified medical physicist at MAASTRO Clinic and full professor at Maastricht UMC+ and Maastricht University, where he holds the chair in Clinical Data Science. His research focuses on three main themes: building global data-sharing infrastructures, machine-learning outcome prediction modelling based on this data, and applying outcome prediction models to improve the lives of patients. His main scientific breakthrough has been the development the Personal Health Train a ‘distributed learning’ infrastructure that does not require data to leave the hospital. This has reduced many of the ethical and other barriers to data sharing.
This lecture is part of traditional series of lectures for alumni: the UM Star Lectures. The other 13 lectures are organized in 13 different cities and 5 countries on the same day, at the same time. This event is organised to reach out to and inspire alumni, share academic insights, experiences and memories, and to create an interconnected UM Alumni Community.
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