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

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SMITH - Smart Medical Information Technology for Healthcare

Medical data routinely generated in everyday clinical practice is processed and made available to medical research in a standardized form. Patients benefit from reliable research results, more precise diagnoses and better treatments. In order to link data from care and research, the participating university hospitals in Aachen, Bonn, Essen, Halle, Hamburg, Jena and Leipzig have established sustainable Data Integration Centers. The network partners Ruhr University Bochum, the Düsseldorf University ...

Programme: MII - Medical Informatics Initiative

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

Start date: 1st Jan 2018

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

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

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#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

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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

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

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 ...

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Implementation of a clinical trial recruitment support system based on fast healthcare interoperability resources (FHIR) in a cardiology department
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Clinical Trial Recruitment Support Systems can booster patient inclusion of clinical trials by automatically analyzing eligibility criteria based on electronic health records. However, missing … interoperability has hindered introduction of those systems on a broader scale. Therefore, our aim was to develop a recruitment support system based on FHIR R4 and evaluate its usage and features in a cardiology department. Clinical conditions, anamnesis, examinations, allergies, medication, laboratory data and echocardiography results were imported as FHIR resources. Clinical trial information, eligibility criteria and recruitment status were recorded using the appropriate FHIR resources without extensions. Eligibility criteria linked by the logical operation “OR” were represented by using multiple FHIR Group resources for enrollment. The system was able to identify 52 of 55 patients included in four clinical trials. In conclusion, use of FHIR for defining eligibility criteria of clinical trials may facilitate interoperability and allow automatic screening for eligible patients at multiple sites of different healthcare providers in the future. Upcoming changes in FHIR should allow easier description of “OR”-linked eligibility criteria.

Authors: Clemens Scherer, Stephan Endres, Martin Orban, Stefan Kääb, Steffen Massberg, Alfred Winter, Matthias Löbe

Date Published: 1st May 2022

Publication Type: Journal article

Multi-institutional breast cancer detection using a secure on-boarding service for Distributed Analytics
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

The constant upward movement of data-driven medicine as a valuable option to enhance daily clinical practice has brought new challenges for data analysts to get access to valuable but sensitive data … due to privacy considerations. One solution for most of these challenges are Distributed Analytics (DA) infrastructures, which are technologies fostering collaborations between healthcare institutions by establishing a privacy-preserving network for data sharing. However, in order to participate in such a network, a lot of technical and administrative prerequisites have to be made, which could pose bottlenecks and new obstacles for non-technical personnel during their deployment. We have identified three major problems in the current state-of-the-art. Namely, the missing compliance with FAIR data principles, the automation of processes, and the installation. In this work, we present a seamless on-boarding workflow based on a DA reference architecture for data sharing institutions to address these problems. The on-boarding service manages all technical configurations and necessities to reduce the deployment time. Our aim is to use well-established and conventional technologies to gain acceptance through enhanced ease of use. We evaluate our development with six institutions across Germany by conducting a DA study with open-source breast cancer data, which represents the second contribution of this work. We find that our on-boarding solution lowers technical barriers and efficiently deploys all necessary components and is, therefore, indeed an enabler for collaborative data sharing.

Authors: Sascha Welten, Lars Hempel, Masoud Abedi, Yongli Mou, Mehrshad Jaberansary, Laurenz Neumann, Sven Weber, Kais Tahar, Yeliz Ucer Yediel, Matthias Löbe, Stefan Decker, Oya Beyan, Toralf Kirsten

Date Published: 1st Apr 2022

Publication Type: Journal article

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

Towards harmonized data quality in the medical informatics initiative - current state and future directions
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Health data from hospital information systems are valuable sources for medical research but have known issues in terms of data quality. In a nationwide data integration project in Germany, health care … data from all participating university hospitals are being pooled and refined in local centers. As there is currently no overarching agreement on how to deal with errors and implausibilities, meetings were held to discuss the current status and the need to develop consensual measures at the organizational and technical levels. This paper analyzes the discovered similarities and differences. The result shows that although data quality checks are carried out at all sites, there is a lack of both centrally coordinated data quality indicators and a formalization of plausibility rules as well as a repository for automatic querying of the rules, for example in ETL processes.

Authors: Matthias Löbe, Gaetan Kamdje-Wabo, Adriana Carina Sinza, Helmut Spengler, Marcus Strobel, Erik Tute

Date Published: 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 execution of phenotypic queries in the Leipzig Health Atlas
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: Alexandr Uciteli, Christoph Beger, Jonas Wagner, Alexander Kiel, Frank A Meineke, Sebastian Stäubert, Matthias Löbe, René Hänsel, Judith Schuster, Toralf Kirsten, Heinrich Herre

Date Published: 1st May 2021

Publication Type: InCollection

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

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: Matthias Löbe, Franz Matthies, Sebastian Stäubert, Frank A Meineke, Alfred Winter

Date Published: 1st 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

FAIR4Health 3LGM2 Reference Modell.z3lgm
FAIR4Health
No description specified

Creators: None

Submitters: Matthias Löbe, Mona Perbix

Data file type: Not specified

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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

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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

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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

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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

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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

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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

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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

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ICIMTH 2022 Presentation
FAIR4Health
No description specified

Creator: Matthias Löbe

Submitter: Matthias Löbe

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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: Methodical Use Case PheP, SMITH - Smart Medical Information Technology for Healthcare, POLAR - Polypharmacy, Drug Interactions, Risks

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

ICIMTH 2022

Assets for the ICIMTH 2022 conference paper in Athens.

Start Date: 1st Jul 2022

End Date: 3rd Jul 2022

Event Website: https://www.icimth.com/

Country: Not specified

City: Athens

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Health Atlas - Local Data Hub/Leipzig

The Health Atlas - Local Data Hub/Leipzig 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.

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