Roland Eils' unit at the BIH consists of three research groups: Artificial Intelligence (Roland Eils), Computational Oncology (Naveed Ishaque), and Health Data (Jürgen Eils and Harald Wagener). The unit is part of the BIH Center for Digital Health, chaired by Roland Eils as founding director of the Center. Roland Eils is also heading the Hub for Innovations in Digital Health, HiDiH, a joint collaboration of his BIH unit and the Health Data Science Unit at the Medical Faculty of Heidelberg University. In addition, Roland Eils is an active member of the Medical Informatics Initiative, where he has founded and coordinated HiGHmed. HiGHmed brings together 10 university medical centers for developing interoperable solutions and infrastructures for processing and sharing of clinical and translational research data.
Roland Eils' department at BIH consists of three working groups: Artificial Intelligence (Roland Eils), Computational Oncology (Naveed Ishaque), Health Data (Jürgen Eils and Harald Wagener). The department is part of the BIH Center for Digital Health; Roland Eils is the chair and founding director of this center.
Artificial Intelligence - ailslab
Roland Eils has assembled a small but highly innovative team of students and scientists venturing into different aspects of digital health. The ailslab focusses on innovative methods from the wider field of artificial intelligence for pioneering digital health applications. At the heart of this lab is the integration of huge and deep datasets from both healthcare and research for tackling pressing issues in health and disease. The ambition is to deepen our understanding of disease mechanisms and to improve diagnosis and treatment of cardiovascular and cancer patients among others. Current projects focus on cardiovascular risk modelling, omni-genetic phenotype models, and building computational frameworks with model-to-data approaches for opening medical data for research purposes. Please visit https://www.hidih.org/research/ailslab for further details.
Naveed Ishaque recently started his own research group in the BIH unit of Roland Eils with research focus on applying computational approaches to understanding the basis of molecular biological heterogeneity in -omics data of human disease. They employ artificial intelligence and data science methods, not only to address the underlying causes of this heterogeneity, but also the interactions between different molecular -omics layers. The team has a strong specialization in the application area of oncology, but is also very interested in immunology and neurodegenerative diseases.
A better understanding of global and local patterns in biological data allows for better differentiation of the mechanistics behind biological and molecular processes from technical noise. As such, the team establishes close ties with experimental collaborators who are able to provide large-scale and high-dimensional datasets profiled using state-of-the-art and exotic profiling techniques, including recent technological advances that are able to resolve single cell, spatial, temporal and genetic heterogeneity.
Please visit https://www.hidih.org/research/computational-oncology for further details on ongoing projects in cancer multiomics and precision oncology, Immunology and allergies, or spatially resolved transcriptomics.
The Heath Data team, headed by Jürgen Eils, focusses on processes in medical informatics and bioinformatics. The team works on the automatization of computational workflows in biomedical research, provides data managing tools and infrastructures that support the fast transfer of new research results into healthcare. A fundamental challenge of a digital healthcare environment is the growing amount of sensitive patient data, e.g., created by smart wearables or whole genome sequencing data. Handling and processing of such huge data sets in daily routine diagnostics requires new infrastructures and IT solutions. Therefore, the team is also working on large-scale IT and cloud solutions, in particular the de.NBI cloud. The Health Data team is located in both Berlin and Heidelberg. Please visit https://www.hidih.org/research/health-data for further information.
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