Mit Big Data zur personalisierten Diabetesprävention

A. Jarasch, A. Glaser, H. Häring, M. Roden, A. Schürmann, M. Solimena, F. Theiss, M. Tschöp, G. Wess, M. Hrabe de Angelis

Publikation: Beitrag in FachzeitschriftÜbersichtsartikelBegutachtung

5 Zitate (Scopus)


Since 1980, the number of people with diabetes has quadrupled worldwide. In Germany alone, almost 7 million people suffer from this metabolic disease and every year, there are up to 500,000 new diagnoses. These numbers show the urgent need for new effective prevention measures and innovative forms of treatment. Digitalization makes it possible to explore the widespread disease of diabetes in a new dimension in order to identify subtypes of diabetes very early on and offer suitable personalized preventive measures. With the establishment of a Digital Diabetes Prevention Center, health and research data from a wide variety of sources could be brought together, analysed and evaluated using innovative information technology (IT) capabilities to identify different diabetes subtypes and offer specific prevention and therapy measures that can be used directly through close cooperation with the population.

Titel in ÜbersetzungBig data for personalized diabetes prevention
Seiten (von - bis)486-492
PublikationsstatusVeröffentlicht - 1 Nov. 2018
Extern publiziertJa


  • Artificial intelligence
  • Medical informatics
  • Prediabetic state
  • Preventive medicine
  • Subtypes


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