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  1. Members
  2.  > Working Group In-Memory Computing for Digital Health

SAHRA Project Publications

  • Freitas da Cruz, H., Schneider, F., Schapranow, M.-P.: Prediction of Acute Kidney Injury in Cardiac Surgery Patients: Interpretation using Local Interpretable Model-agnostic Explanations.Proceedings of the 12th International Conference on Biomedical Engineering Systems and Technologies. bll. 380-387. , Prague, Czech Republic (2019).
     
  • Konak, O., Freitas Da Cruz, H., Thiele, M., Golla, D., Schapranow, M.-P.: An Information and Communication Platform Supporting Analytics for Elderly Care.5th International Conference on Information for Ageing Well, Communication Technologies e Health (2019).
     
  • Freitas da Cruz, H., Horschig, S., Nusshag, C., Schapranow, M.-P.: Prediction of Patient Outcomes after Renal Replacement Therapy in Intensive Care.Proceedings of the 3rd International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing (2018).
     
  • Freitas da Cruz, H., Gebhardt, M., Becher, F., Schapranow, M.-P.: Interactive Data Exploration Supporting Elderly Care Planning.Proceedings of the 10th International Conference on eHealth, Telemedicine, and Social Medicine (2018).
     
  • Schapranow, M.-P.: Die digitale Transformation mitgestalten — Der Datenspendeausweis: Souveräner Umgang mit persönlichen Gesundheitsdaten.Plattform Life Sciences.38--39 (2017).
     
  • Schapranow, M.-P.: Datenspendeausweis für ­Bürger: Ein Plädoyer für mündige Patienten, die die eigenen Gesundheitsdaten am besten verstehen.Management & Krankenhaus. (2016).
     
  • Schapranow, M.-P., Uflacker, M., Sariyar, M., Semler, S., Fichte, J., Schielke, D., Ekinci, K., Zahn, T.: Towards An Integrated Health Research Process: A Cloud-based Approach.Proceedings of The IEEE International Conference on Big Data.2813--2818 (2016).
     
  • Postel, M.: Geographical Exploration of Key Performance Indicators for Elderly Care Planning, (2016).
     
  • Rückert, L.: Real-time Exploration of Healthcare Data using In-Memory Database Technology, (2016).
     
  • Horschig, F.: Prediction of Health Research Data using In-Memory Database Technology, (2016).
     

Hasso Plattner Institute for Digital Health at Mount Sinai (HPI·MS)

In March 2019, the Hasso Plattner Institute for Digital Health at Mount Sinai ( HPI·MS ) was formed as the result of a cooperation agreement between the Mount Sinai Health System (MSHS) in New York City and the Hasso Plattner Institute (HPI). www.hpims.org/

Contact

Chair Representatives

Prof. Dr. med. Erwin Böttinger
Professor for Digital Health - Personalized Medicine and Head of Digital Health Center
erwin.boettinger(at)hpi.de
www.hpi.de/boettinger

Office:

Room: G-2.2.22
Phone.: +49-(0)331 5509-164
Fax: +49-(0)331 5509-163
E-mail: office-boettinger(at)hpi.de

 

Prof. Dr. Bert Arnrich
Professor for Digital Health - Connected Healthcare
www.hpi.de/arnrich

 

Prof. Dr. Christoph Lippert
Professor for Digital Health & Machine Learning

Office:

Room: G-2.1.22
Phone.: +49-(0)331 5509-4850
Fax: +49-(0)331 5509-4849
E-mail: office-arnrich(at)hpi.de / office-lippert (at)hpi.de

Visiting address:

Campus III Building G2
Rudolf-Breitscheid-Straße 187
14482 Potsdam, Germany

Press and media contact:

Saskia Blank
PR Manager Digital Health
+49-(0)331 5509-4862
saskia.blank(at)hpi.de

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08.10.2020 | Neuer Co-Direktor des Hasso Plattner Institute for Digital Health at Mount Sinai

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04.09.2020 | COVID-19: Wissenschaftler warnen vor akutem Nierenversagen

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