Mark Hoogendoorn

Deep Reinforcement Learning in Health Care

In health care, many of the decision made are of a sequential nature. Just think of a doctor continuously modifying the ventilator of an intubated ICU patient or changing the dosage of fluids administered. Such decision can be supported by AI driven models. Deep Reinforcement Learning (DRL) is a very natural fit, however comes with some characteristics that do not fit the medical domain well. In this talk, I will focus on novel developments within DRL to make it better suited for the health domain, and also show some example applications.

Mark Hoogendoorn is a Full Professor of Artificial Intelligence at the Department of Computer Science of the Vrije Universiteit Amsterdam (VU) and chair of the Quantitative Data Analytics group. He obtained his PhD degree in 2007 and was a PostDoc at the University of Minnesota thereafter. He returned to the VU and became an assistant and later an associate professor before moving to his current full professor position. In 2015, he was a visiting scholar at the Massachusetts Institute for Technology (MIT). His main research focus is on machine learning and its applications, the latter primarily applied in the domain of health and wellbeing.

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