Matthias Löbe

About Matthias Löbe:
No description specified

LHA ID: 7WATMT6CAP-3

Location:  Germany

ORCID: https://orcid.org/0000-0002-2344-0426

Joined: 3rd Apr 2020

Expertise: Not specified

Tools: Not specified

help Their tags

Related items

FAIR4Health

FAIR4Health is a Horizon 2020 project which aims to FAIRify medical datasets.

Programme: Science with and for Society (SwafS) in Horizon 2020

Public web page: https://www.fair4health.eu/

Start date: 1st Dec 2019

End date: 30th Nov 2021

SMITH - Smart Medical Information Technology for Healthcare
No description specified

Programme: MII - Medical Informatics Initiative

Public web page: https://www.smith.care/

Start date: 1st Jan 2018

NLP4CR - Natural Language Processing for Clinical Research

The NLP4CR project was initiated as part of Colleen Goldberg's master thesis. Medical information is not always available in a structured form, but as free text documentation. NLP techniques make it possible to analyse, annotate and extract these free texts. In this way, medical data can be made accessible for machine processing and for clinical research.

Programme: This Project is not associated with a Programme

Public web page: http://www.imise.uni-leipzig.de/Gruppen/MIG

Start date: 1st Jan 2015

Evaluation Metadata Repository

The aim of the MDR-Evaluation project was an evaluation of the possible application scenarios for metadata repositories by a larger group of experts. The focus was not on concrete software, but on the community's basic expectation of a web-based database of data elements.

Metadata repositories (MDR) are databases for data elements that can be used both in research, e.g. in clinical studies or epidemiological cohorts, and in care, e.g. in hospital information systems. These data elements are not ...

Programme: This Project is not associated with a Programme

Public web page: http://www.imise.uni-leipzig.de/Gruppen/MIG

Start date: 1st Jan 2014

FAIR4Health Information Architecture
FAIR4Health

Ressource related to the information architecture subsuming the central FAIR4Health Platform and the local FAIR4Health agents.

Submitter: Matthias Löbe

Studies: 3LGM² model for FAIR4Health

Resources: 3LGM² local model DIC Leipzig, 3LGM² model survey, 3LGM² reference model, Diagram inter-level relationships

FAIR4Health Pathfinder Case Studies
FAIR4Health
No description specified

Submitter: Matthias Löbe

Studies: #1 Characterization of multimorbidity patterns and association with heal...

Resources: Clinical Dataset

#1 Characterization of multimorbidity patterns and association with health outcomes in the elderly
FAIR4Health

To achieve the objective of Use Case 1, a retrospective study has been performed with data from 5 EU cohorts in different health care settings (hospital, primary care, nursing homes) and health research organizations:

  1. UNIGE: provides anonymized health care data from the EHR of the University Hospitals of Geneva.
  2. SAS: provides health care data from the EHR of the Virgen del Rocío University Hospital in Seville as part of the Andalusian Health Service.
  3. UCSC: provides health ...

Submitter: Matthias Löbe

Investigation: FAIR4Health Pathfinder Case Studies

Resources: Clinical Dataset

Study type: Secondary data analysis

3LGM² model for FAIR4Health
FAIR4Health
No description specified

Submitter: Matthias Löbe

Investigation: FAIR4Health Information Architecture

Resources: 3LGM² local model DIC Leipzig, 3LGM² model survey, 3LGM² reference model, Diagram inter-level relationships

Study type: Not specified

1 hidden item
Clinical Dataset
FAIR4Health

Clinical data extracted from local EHR systems.

Submitter: Matthias Löbe

Resource type: Experimental Assay Type

Technology type: Technology Type

Investigation: FAIR4Health Pathfinder Case Studies

Study: #1 Characterization of multimorbidity patterns ...

3LGM² reference model
FAIR4Health

The 3LGM² reference model for the FAIR4Health information architecture is based on the 3LGM² Metamodel. A graphical export of the different layers and a matrix view of the inter-level relationships is provided. However the 3LGM² tool is required for an interactive display of the model and additional functions.

Submitter: Matthias Löbe

Biological problem addressed: Model Analysis Type

Investigation: FAIR4Health Information Architecture

Study: 3LGM² model for FAIR4Health

Diagram inter-level relationships
FAIR4Health
No description specified

Submitter: Matthias Löbe

Biological problem addressed: Model Analysis Type

Investigation: FAIR4Health Information Architecture

Study: 3LGM² model for FAIR4Health

3LGM² local model DIC Leipzig
FAIR4Health
No description specified

Submitter: Matthias Löbe

Biological problem addressed: Model Analysis Type

Investigation: FAIR4Health Information Architecture

Study: 3LGM² model for FAIR4Health

1 hidden item
Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and Their Association with Mortality through a Frequent Pattern Growth Association Algorithm
FAIR4Health

Abstract (Expand)

The current availability of electronic health records represents an excellent research opportunity on multimorbidity, one of the most relevant public health problems nowadays. However, it also poses a …t also poses a methodological challenge due to the current lack of tools to access, harmonize and reuse research datasets. In FAIR4Health, a European Horizon 2020 project, a workflow to implement the FAIR (findability, accessibility, interoperability and reusability) principles on health datasets was developed, as well as two tools aimed at facilitating the transformation of raw datasets into FAIR ones and the preservation of data privacy. As part of this project, we conducted a multicentric retrospective observational study to apply the aforementioned FAIR implementation workflow and tools to five European health datasets for research on multimorbidity. We applied a federated frequent pattern growth association algorithm to identify the most frequent combinations of chronic diseases and their association with mortality risk. We identified several multimorbidity patterns clinically plausible and consistent with the bibliography, some of which were strongly associated with mortality. Our results show the usefulness of the solution developed in FAIR4Health to overcome the difficulties in data management and highlight the importance of implementing a FAIR data policy to accelerate responsible health research.

Authors: Jonás Carmona-Pírez, Beatriz Poblador-Plou, Antonio Poncel-Falcó, Jessica Rochat, Celia Alvarez-Romero, Alicia Martínez-García, Carmen Angioletti, Marta Almada, Mert Gencturk, A. Anil Sinaci, Jara Eloisa Ternero-Vega, Christophe Gaudet-Blavignac, Christian Lovis, Rosa Liperoti, Elisio Costa, Carlos Luis Parra-Calderón, Aida Moreno-Juste, Antonio Gimeno-Miguel, Alexandra Prados-Torres

Date Published: 1st Feb 2022

Publication Type: Journal article

Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas.
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles … are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

Authors: A. Uciteli, C. Beger, J. Wagner, A. Kiel, F. A. Meineke, S. Staubert, M. Lobe, R. Hansel, J. Schuster, T. Kirsten, H. Herre

Date Published: 24th May 2021

Publication Type: Journal article

Ontological modelling and FHIR Search based representation of basic eligibility criteria
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Planning clinical studies to check medical hypotheses requires the specification of eligibility criteria in order to identify potential study participants. Electronically available patient data allows … to support the recruitment of patients for studies. The Smart Medical Information Technology for Healthcare (SMITH) consortium aims to establish data integration centres to enable the innovative use of available healthcare data for research and treatment optimization. The data from the electronic health record of patients in the participating hospitals is integrated into a Health Data Storage based on the Fast Healthcare Interoperability Resources standard (FHIR), developed by HL7. In SMITH, FHIR Search is used to query the integrated data. An investigation has shown the advantages and disadvantages of using FHIR Search for specifying eligibility criteria. This paper presents an approach for modelling eligibility criteria as well as for generating and executing FHIR Search queries. Our solution is based on the Phenotype Manager, a general ontological phenotyping framework to model and calculate phenotypes using the Core Ontology of Phenotypes.

Authors: A. Uciteli, C. Beger, J. Wagner, T. Kirsten, F. A. Meineke, S. Staubert, M. Lobe, H. Herre

Date Published: 26th Apr 2021

Publication Type: Journal article

Problems in FAIRifying Medical Datasets.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Despite their young age, the FAIR principles are recognised as important guidelines for research data management. Their generic design, however, leaves much room for interpretation in domain-specific … application. Based on practical experience in the operation of a data repository, this article addresses problems in FAIR provisioning of medical data for research purposes in the use case of the Leipzig Health Atlas project and shows necessary future developments.

Authors: M. Lobe, F. Matthies, S. Staubert, F. A. Meineke, A. Winter

Date Published: 16th Jun 2020

Publication Type: Journal article

Der Leipzig Health Atlas
LHA - Leipzig Health Atlas

Abstract (Expand)

Die Notwendigkeit des Managements von Forschungsdaten ist von der Forschungscommunity erkannt – Sponsoren, Gesetzgeber, Verlage erwarten und fördern die Einhaltung der guten wissenschaftlichen Praxis, … was nicht nur die Archivierung umfasst, sondern auch die Verfügbarkeit von Forschungsdaten- und ergebnissen im Sinne der FAIR-Prinzipien. Der Leipzig Health Atlas (LHA) ist ein Projekt zur Präsentation und zum Austausch eines breiten Spektrums von Publikationen, (bio) medizinischen Daten (z.B. klinisch, epidemiologisch, molekular), Modellen und Tools z.B. zur Risikoberechnung in der Gesundheitsforschung. Die Verbundpartner decken hierbei einen breiten Bereich wissenschaftlicher Disziplinen ab, beginnend von medizinischer Systembiologie über klinische und epidemiologische Forschung bis zu ontologischer und dynamischer Modellierung. Derzeit sind 18 Forschungskonsortien beteiligt (u.a. zu den Domänen Lymphome, Gliome, Sepsis, Erblicher Darm- und Brustkrebs), die Daten aus klinischen Studien, Patientenkohorten, epidemiologischen Kohorten, teilweise mit umfangreichen molekularen und genetischen Profilen, sammeln. Die Modellierung umfasst algorithmische Phänotypklassifizierung, Risikovorhersage und Krankheitsdynamik. Wir konnten in einer ersten Entwicklungsphase zeigen, dass unsere webbasierte Plattform geeignet ist, um (1) Methoden zur Verfügung zu stellen, um individuelle Patientendaten aus Publikationen für eine Weiternutzung zugänglich zu machen, (2) algorithmische Werkzeuge zur Phänotypisierung und Risikoprofilerstellung zu präsentieren, (3) Werkzeuge zur Durchführung dynamischer Krankheits- und Therapiemodelle interaktiv verfügbar zu machen und (4) strukturierte Metadaten zu quantitativen und qualitativen Merkmalen bereit zu stellen. Die semantische Datenintegration liefert hierzu die Technologien (Ontologien und Datamining Werkzeuge) für die (semantische) Datenintegration und Wissensanreicherung. Darüber hinaus stellt sie Werkzeuge zur Verknüpfung eigener Daten, Analyseergebnisse, öffentlich zugänglicher Daten- und Metadaten-Repositorien sowie zur Verdichtung komplexer Daten zur Verfügung. Eine Arbeitsgruppe zur Applikationsentwicklung und –validierung entwickelt innovative paradigmatische Anwendungen für (1) die klinische Entscheidungsfindung für Krebsstudien, die genetische Beratung, für Risikovorhersagemodelle sowie Gewebe- und Krankheitsmodelle und (2) Anwendungen (sog. Apps), die sich auf die Charakterisierung neuer Phänotypen (z.B. ‚omics‘-Merkmale, Körpertypen, Referenzwerte) aus epidemiologischen Studien konzentrieren. Diese Anwendungen werden gemeinsam mit klinischen Experten, Genetikern, Systembiologen, Biometrikern und Bioinformatikern spezifiziert. Der LHA stellt Integrationstechnologie bereit und implementiert die Anwendungen für die User Communities unter Verwendung verschiedener Präsentationswerkzeuge bzw. Technologien (z.B. R-Shiny, i2b2, Kubernetes, SEEK). Dazu ist es erforderlich, die Daten und Metadaten vor dem Hochladen zu kuratieren, Erlaubnisse der Datenbesitzer einzuholen, die erforderlichen Datenschutzkriterien zu berücksichtigen und semantische Annotationen zu überprüfen. Zudem werden die zugelieferten Modellalgorithmen in einer qualitätsgesicherten Weise aufbereitet und, soweit anwendbar, online interaktiv zur Verfügung gestellt. Der LHA richtet sich insbesondere an die Zielgruppen Kliniker, Epidemiologen, Molekulargenetiker, Humangenetiker, Pathologen, Biostatistiker und Modellierer ist aber unter www.healthatlas.de öffentlich zugänglich – aus rechtlichen Gründen erfordert der Zugriff auf bestimmte Applikationen und Datensätze zusätzliche Autorisierung. Das Projekt wird über das BMBF Programm i:DSem (Integrative Datensemantik für die Systemmedizin, Förderkennzeichen 031L0026) gefördert.

Authors: F. A. Meineke, Sebastian Stäubert, Matthias Löbe, C. Beger, René Hänsel, A. Uciteli, H. Binder, T. Kirsten, M. Scholz, H. Herre, C. Engel, Markus Löffler

Date Published: 19th Sep 2019

Publication Type: Misc

Design and Concept of the SMITH Phenotyping Pipeline.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Phenotyping means the determination of clinical relevant phenotypes, e.g. by classification or calculation based on EHR data. Within the German Medical Informatics Initiative, the SMITH consortium is … working on the implementation of a phenotyping pipeline. to extract, structure and normalize information from the EHR data of the hospital information systems of the participating sites; to automatically apply complex algorithms and models and to enrich the data within the research data warehouses of the distributed data integration centers with the computed results. Here we present the overall picture and essential building blocks and workflows of this concept.

Authors: F. A. Meineke, S. Staubert, M. Lobe, A. Uciteli, M. Loffler

Date Published: 3rd Sep 2019

Publication Type: Journal article

Design of Metadata Services for Clinical Data Interoperability in Germany.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Secondary use of electronic health record (EHR) data requires a detailed description of metadata, especially when data collection and data re-use are organizationally and technically far apart. This … paper describes the concept of the SMITH consortium that includes conventions, processes, and tools for describing and managing metadata using common standards for semantic interoperability. It deals in particular with the chain of processing steps of data from existing information systems and provides an overview of the planned use of metadata, medical terminologies, and semantic services in the consortium.

Authors: M. Lobe, O. Beyan, S. Staubert, F. Meineke, D. Ammon, A. Winter, S. Decker, M. Loffler, T. Kirsten

Date Published: 21st Aug 2019

Publication Type: Journal article

Continouus Annotation Quality Control, Support for Hierarchically Structured Label Sets and Long-Segment Annotation with WAT-SL 2.0
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Matthias Löbe, O. Beyan, Sebastian Stäubert, Frank A. Meineke, D. Ammon, Alfred Winter, S. Deckert, Markus Löffler, Toralf Kirsten

Date Published: 2019

Publication Type: InProceedings

Towards a Medication Core Data Set for the Medical Informatics Initiative (MII):Initial Mapping Experience between the German Procedure Classification (OPS) and the Identification of Medicinal Products (IDMP)
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: S. Zabka, D. Ammon, T. Ganslandt, J. E. Gewehr, C. Haverkamp, S. Kiefer, H. Lautenbacher, Matthias Löbe, S. Thun, M. Boeker

Date Published: 2019

Publication Type: InProceedings

Smart Medical Information Technology for Healthcare (SMITH).
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

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 standardsbased 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.

Authors: A. Winter, S. Staubert, D. Ammon, S. Aiche, O. Beyan, V. Bischoff, P. Daumke, S. Decker, G. Funkat, J. E. Gewehr, A. de Greiff, S. Haferkamp, U. Hahn, A. Henkel, T. Kirsten, T. Kloss, J. Lippert, M. Lobe, V. Lowitsch, O. Maassen, J. Maschmann, S. Meister, R. Mikolajczyk, M. Nuchter, M. W. Pletz, E. Rahm, M. Riedel, K. Saleh, A. Schuppert, S. Smers, A. Stollenwerk, S. Uhlig, T. Wendt, S. Zenker, W. Fleig, G. Marx, A. Scherag, M. Loffler

Date Published: 18th Jul 2018

Publication Type: Journal article

FAIR4Health 3LGM2 Reference Modell.z3lgm
FAIR4Health
No description specified

Creators: None

Submitters: Matthias Löbe, Mona Perbix

Data file type: Not specified

Download
SAS metadata
FAIR4Health

This file contains the FHIR CapabilityStatement and FHIR Provenance ressources created within this use case in the local onFHIR store. It covers both #1 Characterization of multimorbidity patterns and association with health outcomes in the elderly and #2 Early prediction service for 30-days readmission risk in COPD patients.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

Download
UP data
FAIR4Health

The dataset contains data from 1,313 patients. It is not available for download here, but registered in the FAIR4Health Platform portal.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

External Link View content
UNIGE data
FAIR4Health

The dataset contains data from 244 patients. It is not available for download here, but registered in the FAIR4Health Platform portal.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

External Link View content
UP metadata
FAIR4Health

This file contains the FHIR CapabilityStatement and FHIR Provenance ressources created within this use case in the local onFHIR store.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

Download
UCSC metadata
FAIR4Health

This file contains the FHIR CapabilityStatement and FHIR Provenance ressources created within this use case in the local onFHIR store.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

Download
SAS data
FAIR4Health

The dataset contains data from 3,786 patients. It is not available for download here, but registered in the FAIR4Health Platform portal.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

External Link View content
UNIGE metadata
FAIR4Health

This file contains the FHIR CapabilityStatement and FHIR Provenance ressources created within this use case in the local onFHIR store.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

Download
UCSC data
FAIR4Health

The dataset contains data from 331 patients. It is not available for download here, but registered in the FAIR4Health Platform portal.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

External Link View content
IACS metadata
FAIR4Health

This file contains the FHIR CapabilityStatement and FHIR Provenance ressources created within this use case in the local onFHIR store.

Creators: None

Submitter: Matthias Löbe

Data file type: Not specified

Download
2 hidden items
NLP for Clinical Research Tool
NLP4CR - Natural Language Processing for Clinical Research

Motivation: By using the NLP4CR tool, medical facts (e.g. diagnoses, laboratory values) can be extracted from German medical full texts.

Description: The NLP4CR tool is a prototype that demonstrates the applicability of Apache UIMA and cTakes to medical full texts in German language.

Creators: Sebastian Stäubert, Matthias Löbe, Colleen Goldberg

Submitter: Christoph Beger

Poster: Der Leipzig Health Atlas
LHA - Leipzig Health Atlas

The need to manage research data is recognised by the research community - sponsors, legislators, publishers expect and encourage good scientific practice, which not only includes archiving, but also the availability of research data and results in line with FAIR principles. The publication gives a brief overview of the Leipzig Health Atlas (LHA), which is a project for the presentation and exchange of a wide range of publications, (bio) medical data (e.g. clinical, epidemiological, molecular), ...

Creators: René Hänsel, Matthias Löbe, Sebastian Stäubert, Christoph Beger

Submitter: Christoph Beger

Download
Abstract: Der Leipzig Health Atlas
LHA - Leipzig Health Atlas

The need to manage research data is recognised by the research community - sponsors, legislators, publishers expect and encourage good scientific practice, which not only includes archiving, but also the availability of research data and results in line with FAIR principles. The publication gives a brief overview of the Leipzig Health Atlas (LHA), which is a project for the presentation and exchange of a wide range of publications, (bio) medical data (e.g. clinical, epidemiological, molecular), ...

Creators: René Hänsel, Matthias Löbe, Sebastian Stäubert, Christoph Beger

Submitter: Christoph Beger

Download
Science with and for Society (SwafS) in Horizon 2020
No description specified

Projects: FAIR4Health

Web page: https://ec.europa.eu/programmes/horizon2020/en/h2020-section/science-and-society

MII - Medical Informatics Initiative

The medical informatics initiative was created to close the gap between research and healthcare. All of Germany’s university hospitals have joined forces with research institutions, businesses, health insurers, and patient advocacy groups to create a framework that harnesses research findings to the direct benefit of patients. The German Federal Ministry of Education and Research (BMBF) is investing around 160 million euros in the programme through 2021. The digitisation of medicine is creating ...

Projects: SMITH - Smart Medical Information Technology for Healthcare, POLAR - Polypharmacy, Drug Interactions, Risks

Web page: https://www.medizininformatik-initiative.de/en

Navigate

Health Atlas

The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

Registered Repository

re3data.org Badge
Powered by
 (v.1.13.0-master)
Leipzig Health Atlas | Funding and Programmes | Credits | Terms & Conditions | Privacy Policy | Imprint
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies