Making Use of Big Data for Personalized Diabetes Prevention

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 up to 500,000 new cases are diagnosed. These figures highlight the urgent need for new, effective prevention measures and innovative forms of treatment. In a recently published article in The Diabetologist, DZD scientists describe how digitization can help to explore the widespread disease of diabetes in a new dimension. The aim is to identify subtypes of this metabolic disease and to develop suitable personalized preventive measures.

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The researchers' idea: With the establishment of a digital diabetes prevention center, health and research data from various sources could be brought together and analyzed and evaluated using innovative information technologies. In this way, different diabetes subtypes could be identified and, building on this, specific prevention and therapy measures for the respective subtypes could be investigated.

Original publication:
A. Jarasch, A. Glaser, H. Häring, M. Roden, A. Schürmann, M. Solimena, F. Theiss, M. Tschöp, G. Wess, M. Hrabe de Angelis (2018): Mit Big Data zur personalisierten Diabetesprävention, Der Diabetologe (pp1-6). Link to publication