Publications

Presentation Slides

Selected Publications

In the following, you can find selected research publications related to our activities applying in-memory technology for life sciences research areas.

Research Publications

  • Ganzinger, M., Glaab, E., Kerssemakers, J., Nahnsen, S., Sax, U., Schaadt, N.S., Schapranow, M.-P., Tiede, T.: Biomedical and Clinical Research Data Management. In: Wolkenhauer, O. (red.) Systems Medicine. bll. 532 - 543. Academic Press, Oxford (2021). 
  • Schapranow, M.-P.: Good News: Wie Data Science dabei hilft, die Corona-Pandemie besser zu verstehen.Portal Wissen: Das Forschungsmagazin der Universität Potsdam.9,14--19 (2020). 
  • 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). 
  • Schapranow, M.-P.: #nCoVStats: Wie Data Science hilft die Coronavirus-Pandemie zu verstehen.gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland.13,34--37 (2020). 
  • 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. bl. 38--48. Association for Computational Linguistics, Online (2020). 
  • da Cruz, H.F., Pfahringer, B., Martensen, T., Schneider, F., Meyer, A., Bottinger, E., Schapranow, M.-P.: Using Interpretability Approaches to Update textquotedblleftBlack-Boxtextquotedblright Clinical Prediction Models: an External Validation Study in Nephrology.Artificial Intelligence in Medicine.101982 (2020). 
  • Stegbauer, J.S., Kraus, M., Nordmeyer, S., Kirchner, M., Ziehm, M.Z., Dommisch, H., Kelle, S., Kelm, M., Baczko, I., Landmesser, U., Tschope, C., Knosalla, C., Falcke, M., Schapranow, M.-P., Regitz-Zagrosek, V., Mertins, P., Kühne, T.: Proteomic analysis reveals upregulation of ACE2, the putative SARS-CoV-2 receptor in pressure- but not volume-overloaded human hearts.Hypertension. (2020). 
  • Kraus, M., Mathew Stephen, M., Schapranow, M.-P.: Eatomics: Shiny exploration of quantitative proteomics data.Journal of Proteome Research. (2020). 
  • Schapranow, M.-P.: Hand in Hand: Wie KI und Ärzte in der Onkologie zusammenarbeiten.Konkrete Anwendungsfälle von KI & Big-Data in der Industrie.69--74 (2020). 
  • 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). 

Further Publications

  • Gather Knowledge in Data Management for Digital Health
    In the past month, the coronavirus pandemic influenced all our lives on a daily basis. At the same time, advances of digital health solution become more and more visible. If you are keen to extend your knowledge about data management for digital health, you should have a look at our lecture “Data Management for Digital ...
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  • nCoVStats: A summer with COVID19
    We have prepared just another animation visualizing the latest developments of Coronavirus spread. It shows  the dramatic worldwide perspective of how fast new hotspots arise, e.g. countries of South America and India. For further details and in-depth analyses, you are invited to use our COVID-19 data analysis tool. COVID-19 worldwide situation from Mar 15 to Oct ...
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  • nCoVStats: A worldwide perspective on six months of COVID19
    We have prepared an animation to visualize the latest development around the Coronavirus spread. It shows  the dramatic worldwide perspective of how vast the amount of infections increases in comparison to the initial hotspot in China. For further details and in-depth analyses, you are invited to use our COVID-19 data analysis tool. COVID-19 worldwide situation from ...
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  • nCoVStats: A worldwide perspective on 4 months of COVID19
    We prepared an animation to visualize the latest coronavirus spread across the globe. It shows for the first time the dramatic worldwide developments once the initial hotspot in China was already isolated. For further details and in-depth analyses, you are invited to use our COVID-19 data analysis tool. COVID-19 worldwide situation from Feb 7 to June ...
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  • nCoVStats: Worldwide Coronavirus Visualization May 15 to June 17, 2020
    We prepared another animation to visualize the latest coronavirus spread across the globe. Bear in mind: it just shows selected days from mid May to mid June 2020. For further details and in-depth analyses, please do not hesitate to try our COVID-19 data analysis tool. COVID-19 worldwide situation from May 15 to June 17, 2020: The situation ...
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  • nCoVStats: Worldwide Coronavirus Visualization May 2 to May 29, 2020
    We prepared another animation to visualize the latest coronavirus spread across the globe. Bear in mind: it just shows selected days of May 2020. For further details and in-depth analyses, please do not hesitate to try our COVID-19 data analysis tool. COVID-19 worldwide situation from May 2 to May 29, 2020: The situation in May 2020: The ...
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  • nCoVStats: Worldwide Coronavirus Visualization Apr 5 to Apr 17, 2020
    We prepared another animation to visualize the dramatic coronavirus spread. Bear in mind: it shows just a ten days timeframe from early April to mid of April. For further analyses, please refer to our COVID-19 data analysis tool. COVID-19 worldwide situation from Apr 5 to Apr 17, 2020: The situation in early April 2020: Former hotspots in ...
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  • nCoVStats: Worldwide Coronavirus Visualization Mar 15 to Mar 30, 2020
    We prepared another animation to visualize the dramatic coronavirus spread. Bear in mind: it shows just a two-weeks timeframe from mid March to end of March. For further analyses, please refer to our COVID-19 data analysis tool. COVID-19 worldwide situation from Mar 15 to Mar 30, 2020: Mid of Mar 2020, the world had a closer look ...
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  • Worldwide COVID-19 pandemic visualization (Feb vs. Mar 2020)
    By the March 11, 2020, the worldwide spread of COVID-19 (formerly known as 2019-ncov) was referenced as a pandemic situation by WHO. The following animated GIFs visualize the impact of the latest developments. In the following, we compare two selected two-week timeframes in correspondence to the incubation period of COVID-19. For further analyses, please refer ...
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  • Better Diagnoses and Therapies
    Learn more about it in the real-world use case oncology just published in the German article “Für bessere Diagnosen und Therapien: Wie Ärzte und KI in der Krebsbehandlung zusammenarbeiten”.
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