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Featured researches published by Matthias Löbe.


Journal of Clinical Bioinformatics | 2015

The Integrated Data Repository Toolkit (IDRT): accelerating translational research infrastructures

Christian R. Bauer; Thomas Ganslandt; Benjamin Baum; Jan Christoph; Igor Engel; Matthias Löbe; Sebastian Mate; Hans-Ulrich Prokosch; Ulrich Sax; Sebastian Stäubert; Alfred Winter

Description The Open Source software i2b2 [1] provides a translational research platform for storing biomedical data and querying these data with a user-friendly interface for researchers (Figure 1). Despite its powerful features, it is lacking user-friendly tools for installation and configuration, the import of source data and the creation of a comprehensive navigational structure (i2b2 ontology). To close these gaps, the Integrated Data Repository Toolkit (IDRT), consisting of three software tools, has been created. The i2b2 Wizard provides a shell GUI for the installation and configuration of i2b2 instances, projects and users. The i2b2 Import Tool offers a GUI for browsing i2b2 projects and importing data in various standard data formats into i2b2 (e.g., textual (CSV), relational (SQL) or structured data (CDISC ODM/XML)), as well as a dedicated extractor for biomaterial data. During import, i2b2 ontologies are automatically created from metadata included in the source data. The i2b2 Ontology Editor (IOE), being part of the i2b2 Import Tool, can be used for enhancing these i2b2 ontologies. Besides standard functions like rearranging, adding, deleting and renaming folders and items, the IOE is capable of augmenting i2b2 ontologies with more advanced i2b2 functions. By utilizing the two windows of the IOE (one showing the unaltered source i2b2 ontology and the other the manually created target i2b2 ontology), mappings can be achieved by simple drag-and-drop operations. For example, start and end dates can be added to items by dragging a date item onto a fact item. Medical terminologies can easily be imported with the IDRT (e. g. ICD-10, LOINC) and can also be mapped via the same drag-and-drop operations to data elements (expandable beyond the supplied terminologies via a regular expression editor in the IOE). The IDRT tools support the more advanced i2b2 functionalities for “fact nesting”, called “modifiers”. Since the i2b2 web browser query application (i2b2 Web Client) does not support simple access and visualization of modifiers, an IDRT plugin was created that is able to display, combine and export related facts. Additional documentation for enhanced i2b2 usage is provided on the IDRT website [2].


computer-based medical systems | 2009

A semantic model for representing items in clinical trials

Roland Mücke; Matthias Löbe; Magnus Knuth; Frank Loebe

The specification of clinical items is a fundamental problem in the planning of a clinical trial. In this paper we present an approach that uses an RDF model in combination with a suite of OWL ontologies to formally describe the structural and conceptual composition of items. We argue that a Semantic Web data model is more flexible than traditional relational models and therefore more appropriate for specifying and managing data variables with regard to data validity and mappings to external medical terminologies.


Methods of Information in Medicine | 2018

Smart Medical Information Technology for Healthcare (SMITH)

Alfred Winter; Sebastian Stäubert; Danny Ammon; Stephan Aiche; Oya Deniz Beyan; Verena Bischoff; Philipp Daumke; Stefan Decker; Gert Funkat; Jan Gewehr; Armin de Greiff; Silke Haferkamp; Udo Hahn; Andreas Henkel; Toralf Kirsten; Thomas Klöss; Jörg Lippert; Matthias Löbe; Volker Lowitsch; Oliver Maassen; Jens Maschmann; Sven Meister; Rafael T. Mikolajczyk; Matthias Nüchter; Mathias W. Pletz; Erhard Rahm; Morris Riedel; Kutaiba Saleh; Andreas Schuppert; Stefan Smers

Summary Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. “Smart Medical Information Technology for Healthcare (SMITH)” is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH’s goals are to establish Data Integration Centers (DICs) at each SMITH partner hospital and to implement use cases which demonstrate the usefulness of the approach. Objectives: To give insight into architectural design issues underlying SMITH data integration and to introduce the use cases to be implemented. Governance and Policies: SMITH implements a federated approach as well for its governance structure as for its information system architecture. SMITH has designed a generic concept for its data integration centers. They share identical services and functionalities to take best advantage of the interoperability architectures and of the data use and access process planned. The DICs provide access to the local hospitals’ Electronic Medical Records (EMR). This is based on data trustee and privacy management services. DIC staff will curate and amend EMR data in the Health Data Storage. Methodology and Architectural Framework: To share medical and research data, SMITH’s information system is based on communication and storage standards. We use the Reference Model of the Open Archival Information System and will consistently implement profiles of Integrating the Health Care Enterprise (IHE) and Health Level Seven (HL7) standards. Standard terminologies will be applied. The SMITH Market Place will be used for devising agreements on data access and distribution. 3LGM 2 for enterprise architecture modeling supports a consistent development process. The DIC reference architecture determines the services, applications and the standards-based communication links needed for efficiently supporting the ingesting, data nourishing, trustee, privacy management and data transfer tasks of the SMITH DICs. The reference architecture is adopted at the local sites. Data sharing services and the market place enable interoperability. Use Cases: The methodological use case “Phenotype Pipeline” (PheP) constructs algorithms for annotations and analyses of patient-related phenotypes according to classification rules or statistical models based on structured data. Unstructured textual data will be subject to natural language processing to permit integration into the phenotyping algorithms. The clinical use case “Algorithmic Surveillance of ICU Patients” (ASIC) focusses on patients in Intensive Care Units (ICU) with the acute respiratory distress syndrome (ARDS). A model-based decision-support system will give advice for mechanical ventilation. The clinical use case HELP develops a “hospital-wide electronic medical record-based computerized decision support system to improve outcomes of patients with blood-stream infections” (HELP). ASIC and HELP use the PheP. The clinical benefit of the use cases ASIC and HELP will be demonstrated in a change of care clinical trial based on a step wedge design. Discussion: SMITH’s strength is the modular, reusable IT architecture based on interoperability standards, the integration of the hospitals’ information management departments and the public-private partnership. The project aims at sustainability beyond the first 4-year funding period.


Methods of Information in Medicine | 2015

Integrated Data Repository Toolkit (IDRT). A Suite of Programs to Facilitate Health Analytics on Heterogeneous Medical Data.

C. R. K. D. Bauer; Thomas Ganslandt; Benjamin Baum; Jan Christoph; Igor Engel; Matthias Löbe; Sebastian Mate; Sebastian Stäubert; Johannes Drepper; Hans-Ulrich Prokosch; Andreas Winter; Ulrich Sax


medical informatics europe | 2009

Foundations of a Metadata Repository for Databases of Registers and Trials

Jürgen Stausberg; Matthias Löbe; Philippe Verplancke; Johannes Drepper; Heinrich Herre; Markus Löffler


Journal of Biomedical Informatics | 2013

The ISO/IEC 11179 norm for metadata registries: Does it cover healthcare standards in empirical research?

Sylvie M. N. Ngouongo; Matthias Löbe; Jürgen Stausberg


medical informatics europe | 2014

A comprehensive clinical research database based on CDISC ODM and i2b2.

Frank A. Meineke; Sebastian Stäubert; Matthias Löbe; Alfred Winter


SWAT4LS | 2009

TIM: A Semantic Web Application for the Specification of Metadata Items in Clinical Research.

Matthias Löbe; Magnus Knuth; Roland Mücke


Methods of Information in Medicine | 2018

Smart Medical Information Technology for Healthcare (SMITH) : Data Integration based on Interoperability Standards

Sebastian Stäubert; Danny Ammon; Stephan Aiche; Oya Deniz Beyan; Verena Bischoff; Philipp Daumke; Stefan Decker; Gert Funkat; Jan Gewehr; Armin de Greiff; Silke Haferkamp; Udo Hahn; Andreas Henkel; Toralf Kirsten; Thomas Klöss; Jörg Lippert; Matthias Löbe; Volker Lowitsch; Oliver Maassen; Jens Maschmann; Sven Meister; Rafael T. Mikolajczyk; Matthias Nüchter; Mathias W. Pletz; Erhard Rahm; Morris Riedel; Kutaiba Saleh; Andreas Schuppert; Stefan Smers; André Stollenwerk


GI-Jahrestagung | 2012

Integrated Data Repository Toolkit: Werkzeuge zur Nachnutzung medizinischer Daten für die Forschung.

Thomas Ganslandt; Ulrich Sax; Matthias Löbe; Johannes Drepper; Christian R. Bauer; Benjamin Baum; Jan Christoph; Sebastian Mate; Matthias Quade; Sebastian Stäubert; Hans-Ulrich Prokosch

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Benjamin Baum

University of Göttingen

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Hans-Ulrich Prokosch

University of Erlangen-Nuremberg

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Jan Christoph

University of Erlangen-Nuremberg

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Sebastian Mate

University of Erlangen-Nuremberg

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Thomas Ganslandt

University of Erlangen-Nuremberg

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Ulrich Sax

University of Göttingen

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Oya Deniz Beyan

National University of Ireland

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