Tag Archives: Hannover Medical School

HiGHmed Medical Informatics Consortium

Executive Summary

The HiGHmed consortium aims to develop and use innovative information infrastructures to increase the efficiency of clinical research and to swiftly translate research results into validated improvements of patient care. These aims are tightly connected with challenges to integrate and further develop solutions of innovative, internationally interoperable data integration and methods, with the aim to demonstrate their added value for health research and patient care. The concepts must be designed in a way that will help to develop sustainable structures and with the perspective for an easy roll-out to other hospitals. You might want to refer to the HiGHmed consoritum website for further details.

Project Partners

  • Heidelberg University Hospital (UKL-HD)
  • University Medical Center Göttingen (UMG)
  • Hannover Medical School (MHH)
  • University Hospital Schleswig-Holstein / Kiel University (UKSH)
  • University Hospital Cologne (UKK)
  • Universitätsklinikum Würzburg (UKW) / Julius-Maximilians-Universität Würzburg (JMU)
  • Charité Universitätsmedizin Berlin
  • University of Münster (WWU) / University Hospital Münster (UKM)
  • TU Braunschweig (TU-BS)
  • TU Darmstadt (TUD)
  • Heilbronn University (HHN)
  • Helmholtz Center for Infection Research (HZI)
  • Robert Koch-Institut (RKI)
  • German Cancer Research Center (DKFZ)
  • HAWK Hochschule Hildesheim/Holzminden/Goettingen (HAWK-HHG)
  • Hochschule Hannover – University of Applied Sciences and Arts (HSH)
  • Ada Health GmbH
  • InterComponentWare AG (ICW)
  • NEC
  • Siemens Healthcare GmbH
  • Carl-Thiem-Klinikum Cottbus
  • Hasso Plattner Institute and AnalyzeGenomes.com

Publications

Research Publications

  • 1.Rasheed, A., Borchert, F., Kohlmeyer, L., Henkenjohann, R., Schapranow, M.-P.: A Comparison of Concept Embeddings for German Clinical Corpora. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). bll. 2314–2321 (2021). 
  • 2.Henkenjohann, R., Bergner, B., Borchert, F., Bougatf, N., Hund, H., Eils, R., Schapranow, M.-P.: An Engineering Approach towards Multi-Site Virtual Molecular Tumor Board Software Support. Proceedings of the 1st Conference on ICT for Health, Accessibility and Wellbeing. Springer International Publishing (2021). 
  • 3.Borchert, F., Meister, L., Langer, T., Follmann, M., Arnrich, B., Schapranow, M.-P.: Controversial Trials First: Identifying Disagreement Between Clinical Guidelines and New Evidence. AMIA Annual Symposium Proceedings. bll. 236–245 (2021). 
  • 4.Borchert, F., Mock, A., Tomczak, A., Hügel, J., Alkarkoukly, S., Knurr, A., Volckmar, A.-L., Stenzinger, A., Schirmacher, P., Debus, J., Jäger, D., Longerich, T., Fröhling, S., Eils, R., Bougatf, N., Sax, U., Schapranow, M.-P.: Knowledge bases and software support for variant interpretation in precision oncology. Briefings in Bioinformatics. 22, (2021). 
  • 5.Borchert, F., Lohr, C., Modersohn, L., Hahn, U., Langer, T., Wenzel, G., Follmann, M., Schapranow, M.-P.: "Herr Doktor, verstehen Sie mich?“: Wie lernende Systeme helfen medizinische Fachsprache zu verstehen und welche Rolle klinische Leitlinien dabei spielen. gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland. 13, 19–22 (2020). 
  • 6.Borchert, F., Lohr, C., Modersohn, L., Langer, T., Follmann, M., Sachs, J.P., Hahn, U., Schapranow, M.-P.: GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines. Proceedings of the 11th International Workshop on Health Text Mining and Information Analysis. bll. 38–48. Association for Computational Linguistics, Online (2020). 

Events

Sponsors

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