Welcome to the DZD HeaDS Wiki, the central information hub for the DZD HeaDS program!
This wiki supports participants, buddies and organizers by providing clear guidance, key resources, and up-to-date information throughout the program.
DZD HeaDS is a two-year advanced training program coordinated by the German Center for Diabetes Research (DZD), designed for STEM students and early-career doctoral researchers interested in data-driven health research.
The program combines a modular curriculum, hands-on experience, and interdisciplinary networking with a focus on health data, diabetes, and metabolism research.
Data-driven research plays a major role in metabolism research due to the high prevalence of diseases such as diabetes and obesity and the associated extensive and diverse availability of data. The German Center for Diabetes Research (DZD) is a national research network that combines various disciplines, such as translational and clinical research, epidemiology, and computational biomedicine (www.dzd-ev.de). Numerous clinical and cohort-based studies, extensive studies in model organisms, and real-world data thanks to modern technologies such as continuous glucose monitors and their real-time data generation offer an attractive field for data-driven analyses and AI applications. This enables application-oriented learning and research projects that are closely related to patients.
Recent advances in the digitization of the German healthcare system, such as electronic patient records, the Health Data Use Act, and the European Health Data Space (EHDS), hold great potential for data-driven health research. This development generates concrete support needs in the targeted further training of researchers and in the additional recruitment of specialist staff in order to enable high-quality research and novel analyses, as well as to ensure responsible data use. The focus of the DZD HeaDS program here is therefore:
(1) the provision and use of health data through (cross-institutional) data infrastructures,
(2) methods of data integration and analysis of large amounts of data (big data) based on this, using state-of-the-art methods from artificial intelligence and machine learning
(3) the innovation potential of translational, data-driven health research and the concrete translation of research findings into clinical application.
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If you are new to the program, we recommend starting with the Onboarding page.
If you cannot find the information you are looking for or notice something that should be updated, please reach out to the HeaDS coordination team via: heads@dzd-ev.de