@article{TanskiBergstedtBevingtonetal.2019,
  author    = {Tanski, George and Bergstedt, Helena and Bevington, Alexandre and Bonnaventure, Philip and Bouchard, Frederic and Coch, Caroline and Dumais, Simon and Evgrafova, Alevtina and Frauenfeld, Oliver W. and Frederick, Jennifer and Fritz, Michael and Frolov, Denis and Harder, Silvie and Hartmeyer, Ingo and Heslop, Joanne and Hoegstroem, Elin and Johansson, Margareta and Kraev, Gleb and Kuznetsova, Elena and Lenz, Josefine and Lupachev, Alexey and Magnin, Florence and Martens, Jannik and Maslakov, Alexey and Morgenstern, Anne and Nieuwendam, Alexandre and Oliva, Marc and Radosavljevi, Boris and Ramage, Justine Lucille and Schneider, Andrea and Stanilovskaya, Julia and Strauss, Jens and Trochim, Erin and Vecellio, Daniel J. and Weber, Samuel and Lantuit, Hugues},
  title     = {The Permafrost Young Researchers Network (PYRN) is getting older},
  series = {Polar record},
  volume    = {55},
  journal   = {Polar record},
  number    = {4},
  publisher = {Cambridge Univ. Press},
  address   = {New York},
  issn      = {0032-2474},
  doi       = {10.1017/S0032247418000645},
  pages     = {216 -- 219},
  year      = {2019},
  abstract  = {A lasting legacy of the International Polar Year (IPY) 2007-2008 was the promotion of the Permafrost Young Researchers Network (PYRN), initially an IPY outreach and education activity by the International Permafrost Association (IPA). With the momentum of IPY, PYRN developed into a thriving network that still connects young permafrost scientists, engineers, and researchers from other disciplines. This research note summarises (1) PYRN's development since 2005 and the IPY's role, (2) the first 2015 PYRN census and survey results, and (3) PYRN's future plans to improve international and interdisciplinary exchange between young researchers. The review concludes that PYRN is an established network within the polar research community that has continually developed since 2005. PYRN's successful activities were largely fostered by IPY. With >200 of the 1200 registered members active and engaged, PYRN is capitalising on the availability of social media tools and rising to meet environmental challenges while maintaining its role as a successful network honouring the legacy of IPY.},
  language  = {en}
}
@article{FreitasdaCruzPfahringerMartensenetal.2021,
  author    = {Freitas da Cruz, Harry and Pfahringer, Boris and Martensen, Tom and Schneider, Frederic and Meyer, Alexander and B{\"o}ttinger, Erwin and Schapranow, Matthieu-Patrick},
  title     = {Using interpretability approaches to update "black-box" clinical prediction models},
  series = {Artificial intelligence in medicine : AIM},
  volume    = {111},
  journal   = {Artificial intelligence in medicine : AIM},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0933-3657},
  doi       = {10.1016/j.artmed.2020.101982},
  pages     = {13},
  year      = {2021},
  abstract  = {Despite advances in machine learning-based clinical prediction models, only few of such models are actually deployed in clinical contexts. Among other reasons, this is due to a lack of validation studies. In this paper, we present and discuss the validation results of a machine learning model for the prediction of acute kidney injury in cardiac surgery patients initially developed on the MIMIC-III dataset when applied to an external cohort of an American research hospital. To help account for the performance differences observed, we utilized interpretability methods based on feature importance, which allowed experts to scrutinize model behavior both at the global and local level, making it possible to gain further insights into why it did not behave as expected on the validation cohort. The knowledge gleaned upon derivation can be potentially useful to assist model update during validation for more generalizable and simpler models. We argue that interpretability methods should be considered by practitioners as a further tool to help explain performance differences and inform model update in validation studies.},
  language  = {en}
}