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Research & Impact

Shaping the Future of Healthcare Through Research and Innovation

Dive into the diverse research activities at BI-K, where interdisciplinary teams work at the intersection of medicine, data, and technology. Our projects, tools, and collaborations drive progress in digital health and create real-world impact across clinical practice and scientific discovery.

Discover our Research Fields

Research Fields

Our research spans a wide range of fields at the intersection of computer science, data, and medicine. We explore topics such as AI for clinical decision-making, biomedical data integration, and ethical aspects of digital health. These focus areas guide our projects and shape the direction of our interdisciplinary collaborations. Discover how we turn scientific questions into real-world impact.

AI Ethics and Societal Aspects of Biomedical Informatics

The rapid growth of biomedical data and AI-driven methods raises fundamental ethical challenges. Our research addresses issues such as algorithmic bias and the responsible use of sensitive health information. By integrating ethical reflection into technical development, we strive to ensure that biomedical informatics not only advances scientific innovation but also safeguards trust, fairness, and societal responsibility.

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Data Integration, Interoperability & Standards

High-quality medical AI depends on data that is not only accurate, but also consistent, connected, and usable across systems. Therefore, we focus on integrating heterogeneous data sources, ensuring interoperability, and advancing the use of open standards. By harmonizing clinical information from clinical records we enable reliable analytics, reproducible research, and scalable AI solutions. This work lays the foundation for transforming fragmented healthcare data into meaningful insights that support better decision-making, improved patient outcomes, and more efficient workflows.

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Biosignals

Biosignals are time-series data derived, among others, from the heart, nerves, the brain or muscles. Biosignal research in medicine requires complex collaborative work, starting from the support of efficient clinical flows and data integration processes, through employing advanced engineering methods for signal processing, exploring the low-dimensional signal representations and quality control [...]

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Large Language Models

Large Language Models are transforming the way we process and understand biomedical data. In our research, we study how these models can be adapted to the specific challenges of medicine and life sciences—for example, by extracting knowledge from clinical records, supporting structured data integration, or assisting healthcare professionals with decision-making. At the same time, we critically assess the limitations of LLMs to ensure their applications remain robust, transparent, and safe for real-world use.

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Our Research Outcomes & Products

Tools & Services

Our research leads to practical outcomes in the form of software tools, scalable services, and innovative products. These solutions are developed in close collaboration with users from science and healthcare. Whether it’s a data integration platform, a clinical decision-support tool, or a secure analytics environment — our results are designed for real-world application. Explore how we translate ideas into action.

Symbolic Image - Research Data Management

Consulting and Training in Research Data Management

This service brings together expert consulting and focused training to support good research data management in practice. Researchers receive tailored advice for their specific projects, alongside hands-on training that develops skills in data planning, documentation, storage, and reuse. The aim is to promote reproducibility, improve data quality, and support compliance with funder, institutional, and ethical requirements.

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FAIRspace Cologne

FAIRspace Cologne is a GitHub-based platform offering practical guidance, tools, and community resources to support FAIR and effective research data management.

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FAIRdata Cologne

FAIRdata Cologne is a Dataverse-based metadata catalogue for documenting and discovering experimental research activities. It supports collaboration within projects such as CRCs and, where desired, increases the visibility of laboratory research to the wider scientific community.

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Learn about our Research Groups

Research Groups

Our interdisciplinary research groups bring together experts from medicine, computer science, and the life sciences. Each group focuses on a specific aspect of digital health, from distributed analytics to research data management. Through close collaboration, they create synergies that drive both scientific discovery and practical innovation. Meet the teams behind our work.

Research Data Management

Susanne Vorhagen

At the Institute for Biomedical Informatics, our Research Data Management (RDM) team plays a key role in enabling the effective, sustainable, and FAIR (Findable, Accessible, Interoperable, Reusable) handling of medical and biomedical research data. We work closely with researchers, clinicians, and data stewards to ensure that data is collected, documented, and structured in a way that supports reproducible science and downstream reuse [...]

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Distributed Analytics

Mehrshad Jaberansary

Our Distributed Analytics (DA) team focuses on enabling privacy-preserving machine learning on sensitive medical patient data. We develop technologies that allow institutions to collaboratively analyze patient data - such as electronic health records or imaging data - without the need to centralize it. This is particularly crucial in healthcare settings, where data privacy and sovereignty are paramount. [...]

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Our Publications

Publications

Our publications reflect the scientific foundation and collaborative spirit of our work. We contribute to peer-reviewed journals, conferences, and interdisciplinary reports. These outputs document our progress, share insights, and help shape the future of healthcare innovation. Browse our latest research findings.

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Featured Publications

Research

Our Projects

Projects

Our projects turn research ideas into concrete solutions for healthcare and biomedical science. They range from basic research to applied development and are often carried out in close collaboration with partners. Each project reflects our commitment to interdisciplinary, impactful, and responsible innovation. Learn more about what we’re working on.

NFDI4Health

The objective of "Nationale Forschungsdateninfrastruktur for Health" (NFDI4Health) is the amalgamation of epidemiological, public health and clinical research. Therefore, we will develop a research data infrastructure for personal health data.

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Restless

RESTLESS is an ambitious project that brings together Higher Education Institutions (HEIs) and Small and Medium Enterprises (SMEs) from Poland, Germany, Portugal, Greece, and Cyprus. Over a span of 24 months, we’re dedicated to crafting a transformative training programme focused on empowering university students and graduates with entrepreneurial, digital, and green skills. [...]

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FAIR4Rare

There are more than 6,000 diseases, each of which is extremely rare. In total, however, several million people are affected in Germany alone. A disease is considered “rare” if it affects no more than five in 10,000 people. The National Register for Rare Diseases (NARSE) serves to record as many affected people as possible in the long term in order to determine the health effects and care structures of these diseases in Germany. [...]

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Meet our Collaborators

Collaborators

Collaboration is central to our research philosophy. We work with clinical teams, academic institutions, and industry partners at local, national, and international levels. These networks help us scale our impact and develop solutions that are grounded in real-world needs. Discover who we work with to shape the future of healthcare.

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Quicklinks

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