Medical Informatics

A list of our publications can be found here. 

As part of various degree programs we offer the following courses and seminars on a regular basis: 

SS 2024: Module "Clinical Research Informatics", Master's Program Computer Science, HU Berlin. Further information

SS 2023 - 2024: Module "Modern Methods and Applications of Medical Informatics", Health Data Sciences PhD Program, Charité, Master's Program in Epidemiology, Charité / BSPH, Master’s Program in Public Health, Charité / BSPH, Doctorate Environment, Charité. Further information

WS 2020 - SS 2024: Seminar "Current Topics in Medical Informatics", PhD program, Charité. Further information

SS 2020 - 2023: Module "Introduction to Medical Informatics", Master's Program in Epidemiology, Charité. Further information

In addition, we regularly contribute individual courses to various teaching formats such as "Artificial Intelligence in Medicine" (Medicine, Charité), MET3 (PhD program in Health Data Sciences, Charité), "Ethics and Policy Questions" (Master's program in Bioinformatics, FU Berlin) and "Applied Medical Informatics" (Master's program in Epidemiology, Charité / BSPH).

You can find our open source software on our GitHub page. We further develop and operate services for the integration, analysis, and sharing of health data at BIH and Charité. Key examples include:

• Central access point for decentralized analyses, based on DataSHIELD, for privacy-preserving statistical evaluations across distributed data sources.
• Clinical Data Warehouse platform with self-service analytics capabilities, based on Informatics for Integrating Biology and the Bedside (i2b2), for example for BeLOVE.
• Real-World-Evidence platform, built upon the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and tools from the Observational Health Data Science and Informatics (OHDSI) program, connected to the European Health Data Evidence Network (EHDEN).
• Data integration solutions connected to the national platform of the Medical Informatics Initiative (MII) in collaboration with the Medical Data Integration Center (MeDIC) associated with us.
• Platform for capturing study data and Patient-Reported Outcome Measures based on the OpenEDC software of the University Hospitals of Münster and Heidelberg.
• Consulting and technical solutions related to the anonymization and pseudonymization of medical data, including with our anonymization tool ARX.
• Information infrastructures and research data management solutions, for example, for the SFB 1340 in partnership with the Clinic for Radiology and the Institute for Medical Informatics.

PrivateAIM: The goal of the PrivateAIM project is to develop a federated platform for privacy-preserving machine learning and data analytics in the MII. The general concept is that the analyses will come to the data, not the data to the analyses. 
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PCOR-MII: The goal of the PCOR-MII project is it to establish the digital recording of patient-reported outcomes (PROs) in clinics and to integrate them into the national core data set of the medical informatics initiative. The recording of PROs allows the subjective health status of patients to be systematically included in patient care and research. 
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HiGHmed: The partner sites of the HiGHmed consortium in the German Medical Informatics Initiative (MII) establish Medical Data Integration Centers (MeDICs), which integrate and harmonize data from healthcare and research systems. Important tasks include ensuring data quality and data protection to enable data sharing using the MII infrastructure. The added value of the solutions established will be demonstrated in various clinical and research use cases. 
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RISK PRINCIPE: The objective of this project is the development and implementation of a data-driven, risk-stratified infection control process using an automated monitoring system to effectively and efficiently minimize hospital bacteremias. 

GeMTeX: The project's goal is to create a large annotated corpus of German medical texts from patient care, making them accessible in anonymized form for research. 

Somnolink is an interdisciplinary project dedicated to the treatment of obstructive sleep apnoea (OSA) - a widespread disease that affects an estimated 26 million people in Germany. Despite its prevalence, OSA is often underdiagnosed but can have serious health effects if left untreated. As part of Somnolink, the existing infrastructure of the Medical Informatics Initiative (MII) is being expanded in order to integrate sleep data across different sectors and make it available for research. The aim is to improve diagnosis, treatment and therapy adherence for sleep-related illnesses, in particular obstructive sleep apnoea. 
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Open Medical Inference: The project's aim is to simplify the use of AI in medicine by establishing a network of providers offering their AI models as "turnkey" services.

NUM-RDP: The NUM-RDP project operates a central platform for the aggregation and use of routine healthcare data in the University Medicine Network. It forms the technical basis for existing and future research projects that want to use the platform or and/or extend it with new software components. It receives, stores and provides data in an interoperable, open format. The Medical Informatics Group supports the project in the area of technical data protection and information security. 

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NUM-DIZ: In the "NUM-DIZ" project, the Data Integration Centers established at the university hospitals as part of the Medical Informatics Initiative are operated as an infrastructure within the Network of University Medicine.

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ARX is a comprehensive open source software for anonymizing health data. It supports a wide variety of risk models, data transformation techniques and methods for analyzing the usefulness of output data. The software has been used in a variety of contexts, including commercial big data analytics platforms, research projects, clinical trial data sharing and for training purposes. ARX is able to handle large datasets on commodity hardware and it features an intuitive cross-platform graphical user interface. 

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The H2O project brings together more than 23 partners with the aim to improve the quality of care for patients by creating health outcomes observatories that will collect standardised health data in an ethical and a socially responsible way. National observatories will be federated to create a pan-European network for health outcomes data with the purpose of engaging patients and connecting providers, ultimately equipping different stakeholders with the necessary data to improve patient care.

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In the project "AI-based Anonymization in Medicine" (KI-AIM), an anonymization platform is being developed to provide large amounts of realistic health data. Ideally, these data are not persomal and can therefore be used more easily under data protection law. This could facilitate access to data for research and the commercial development of data-based medical solutions. 

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The National Research Data Infrastructure (NFDI) will systematically catalog, sustainably maintain and make databases from science and research accessible and interconnect them (inter)nationally. In this context, the goals of NFDI4Health include (1) enabling the findability of and the accessibility to structured health data, (2) establishing and improving the interoperability and reusability of health data and (3) enabling the sharing and linkage of health data while complying with data protection requirements. 

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The Collaborative Research Center (CRC) 1340 "Matrix in Vision" investigates innovative methods for in vivo visualization of the pathologically altered extracellular matrix. Our group supports the CRC with research data management, analysis and visualization through an information infrastructure project. Here, the focus is on the entire lifecycle of different types of complex and multidimensional data. 

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The aim of the THS-MED project is to develop highly scalable open source tools for trust centers in translational medicine. A key focus is on components for patient data management and pseudonymization, both for study personnel and researchers, as well as for programmatic access.

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CORD_MI: The Medical Informatics Initiative’s (MII) “Collaboration on Rare Diseases” (CORD_MI) aims to improve healthcare and research in the area of rare diseases. To achieve these goals, the technical as well as organizational solutions of the four consortia of the MII (DIFUTURE, HiGHmed, MIRACUM, SMITH) are utilized to share data on a nationwide scale. 

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The project "National Research Data Platform" (CODEX) of the Research Network of University Medicine on COVID-19 (NUM) aims to establish a secure and interoperable national data platform for research on SARS-CoV-2 and COVID-19. This will foster research on the current and future pandemics, as scientists from a wide range of disciplines will be able to quickly access a large number of standardized datasets. 

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In CODEX+ the collaborative research infrastructure CODEX of the Network University Medicine (NUM) will be rolled out more broadly and developed further, with a focus on new data sources, common data models, data anonymisation and convergence with the structures of the Medical Informatics Initiative and further NUM projects. 

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The European Health Data & Evidence Network (EHDEN) aims to answer research questions based on large data sets distributed across Europe while preserving the anonymity of patients. With support from EHDEN, the Charité is building an infrastructure based on the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and the associated tools of the Observational Health Data Sciences and Informatics (OHDSI) program to make health data accessible for research in a structured form. 

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The European Joint Programme on Rare Diseases (EJP RD) brings together over 130 institutions from 35 countries to create a comprehensive, sustainable ecosystem for research, care and medical innovation in the area of rare diseases. In the project, the BIH Medical Informatics Group works on tools and methods supporting sustainable data sharing with a specific focus on privacy aspects. 

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The establishment of the German Research Data Centre (Forschungsdatenzentrum; FDZ) at the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte; BfArM) promises to significantly improve the secure use of health data for research purposes in Germany. As part of this process the BIH Medical Informatics Group participates in a project investigating innovative data anonymization and synthetization techniques, with the aim of ensuring the best possible protection of patient privacy. 

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The Lean European Open Survey on SARS-CoV-2 (LEOSS) is a European non-interventional prospective cohort study on the epidemiology and clinical course of SARS-COV-2 infections. The objective is to further develop evidence-based diagnostic and therapeutic recommendations. Our group contributes to this project by developing and implementing multiple layers of safeguards to support privacy-preserving data sharing. 

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ORCHESTRA is a large-scale research project aimed at combating the coronavirus pandemic. The aim is to establish an international cohort for conducting retrospective and prospective studies in order to generate rigorous evidence to improve the prevention and treatment of COVID-19 and to be better prepared for future pandemics.

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