Benjamin Skov Kaas-Hansen

Benjamin Skov Kaas-Hansen

Ph. D.-student

Benjamin is a hybrid medical doctor and data scientist with an MSc in epidemiology and biostatistics, currently pursuing a PhD in clinical pharmacology and medical informatics at University of Copenhagen. The aim of his research is to leverage longitudinal electronic medical records and registry data to give actionable answers to substantial pharmacovigilance questions. He is interested in causal inference, Bayesian methods, machine learning, and data visualisation and standardisation; R fluent, proficient in Python and SQL, and learning Julia.

Udvalgte publikationer

  1. Udgivet

    Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records

    Thorsen-Meyer, H., Nielsen, A. B., Nielsen, A. P., Kaas-Hansen, Benjamin Skov, Toft, P., Schierbeck, J., Strøm, T., Chmura, Piotr Jaroslaw, Heimann, M., Dybdahl, L., Spangsege, L., Hulsen, P., Belling, Kirstine G, Brunak, Søren & Perner, Anders, 2020, I: The Lancet Digital Health. 2, 4, s. e179–91 13 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  2. Udgivet

    Heterogeneity of treatment effect of prophylactic pantoprazole in adult ICU patients: a post hoc analysis of the SUP-ICU trial

    Granholm, A., Marker, S., Krag, M., Zampieri, F. G., Thorsen-Meyer, H., Kaas-Hansen, Benjamin Skov, van der Horst, I. C. C., Lange, Theis, Wetterslev, J., Perner, Anders & Møller, Morten Hylander, 2020, I: Intensive Care Medicine. 46, s. 717–726 10 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

ID: 185059892