Big data for personalized diabetes prevention

被引:5
|
作者
Jarasch, A. [1 ]
Glaser, A. [1 ]
Haering, H. [1 ,2 ]
Roden, M. [1 ,3 ]
Schuermann, A. [1 ,4 ]
Solimena, M. [1 ,5 ]
Theiss, F. [1 ,6 ]
Tschoep, M. [1 ,7 ]
Wess, G. [1 ,8 ]
de Angelis, M. Hrabe [1 ,9 ]
机构
[1] Helmholtz Zentrum Munchen, DZD, Ingolstadter Landstr 1, D-85764 Neuherberg, Germany
[2] Eberhard Karls Univ Tubingen, Inst Diabetesforsch & Metabol Erkrankungen Hel, Tubingen, Germany
[3] Deutsch Diabet Zentrum, Dusseldorf, Germany
[4] Deutsch Inst Ernahrungsforsch Potsdam Rehbruck, Nuthetal, Germany
[5] Tech Univ Dresden, Paul Langerhans Inst Helmholtz Zentrums Munchen, Univ Klinikum Carl Gustav Carus, Dresden, Germany
[6] Helmholtz Zentrum Munchen Deutsch Forschungszentr, Inst Comp Biol, Neuherberg, Germany
[7] Helmholtz Zentrum Munchen Deutsch Forschungszentr, Inst Diabet & Obes, Neuherberg, Germany
[8] Helmholtz Zentrum Munchen Deutsch Forschungszentr, Neuherberg, Germany
[9] Helmholtz Zentrum Munchen Deutsch Forschungszentr, Inst Expt Genet, Neuherberg, Germany
来源
DIABETOLOGE | 2018年 / 14卷 / 07期
关键词
Prediabetic state; Subtypes; Preventive medicine; Medical informatics; Artificial intelligence;
D O I
10.1007/s11428-018-0384-1
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Since 1980, the number of people with diabetes has quadrupled worldwide. In Germany alone, almost 7million 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 anew dimension in order to identify subtypes of diabetes very early on and offer suitable personalized preventive measures. With the establishment of aDigital Diabetes Prevention Center, health and research data from awide 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.
引用
收藏
页码:486 / 492
页数:7
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