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About the Department Medical Informatics

Brief description and mission statement of the Department

Medical Informatics is an interdisciplinary research group within the Erasmus MC, University Medical Center Rotterdam. The group studies new methods for acquiring, representing, processing, and managing data and knowledge in health care and  the biomedical sciences.

Our research clusters around three main themes: Structuring Medical Data, Structuring Medical Knowledge, and, in combination with the Department of Radiology, Image processing.

In our research line Structuring Medical Data we concentrate on the nature and structure of medical data. Different usage of data creates different demands: data requirements in the context of a clinical trial are different than those in the context of management or quality assurance. Experience has shown that data recorded for one purpose may not be valid or suitable for another purpose. In our research, we address this issue of using data for multiple purposes. Our domain of interest is the electronic patient record. Our objective is to record data in the context of clinical care with sufficient detail so that the data can also be used for other purposes, such as scientific research, quality assurance or management. We focus on generic models that are applicable to different specialities. The models, however, have to be usable in daily practice. Therefore, an essential part of this research is the validation of these models in daily care. Once electronic patient records are available, our research focus shifts to the actual use of the data for multiple purposes. In close collaboration with clinicians, we study systems aimed at improving the  quality of care. Together with other disciplines we also analyze observational databases and study issues involved in naturalistic trials.

In our researchline Structuring Medical Knowledge we investigate the formalization of medical knowledge; that is, the description of knowledge according to a formal representation so that the knowledge can be made operational in a computer system. We do not limit ourselves to knowledge that is provided by experts or is described in journals or books, but also focus on the (semi)automatic extraction of knowledge from documented databases. With respect to documented databases, attention is paid to automated learning techniques for modeling medical knowledge tailored to the specific problems in the medical domain. This includes research in the representation and use of uncertainty in medical knowledge, extracting information from literature and annotated biomolecular data sets ('text-based searching') and supporting the interpretation of data ('data mining'). It is of importance to test the results of our research (both methodology and prototypes of systems) in the various application domains for their usability, in close collaboration with other investigators and clinical partners.

Together with the Department of Radiology of the Erasmus MC, we formed the BIGR (Biomedical Imaging Group) that focuses on innovative fundamental and applied research in biomedical image analysis and computer assisted interventions. The research of BIGR is organized along five research lines: (a) Cardiovascular image analysis, (b) Cellular and molecular image analysis, (c) Neuro image analysis, (d) Image analysis in oncology, (e) Image guided interventions.