Frank A. Meineke

About Frank A. Meineke:
No description specified

LHA ID: 7Y2WRUR7JJ-9

Location:  Germany

ORCID: https://orcid.org/0000-0002-9256-7543

Joined: 2nd Dec 2019

Expertise: Not specified

Tools: Not specified

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Related items

Project Test Demonstrator

Project for testing requests and functions of LHA

Programme: This Project is not associated with a Programme

Public web page: Not specified

Start date: 31st Mar 2021

BASALIT

Coordinating investigators Prof. Dr. Jan C. Simon Prof. Dr. Regina Treudler Klinik für Dermatologie, Venerologie und Allergologie, Universitätsklinikum Leipzig

Sponsor Universität Leipzig Ritterstr. 26, 04109 Leipzig

EudraCT: 2009-011737-27

Programme: University Leipzig (Sponsor)

Public web page: Not specified

STOP-NUC

Coordinating investigator: Prof. Dr. Florian van Bömmel Sektion Hepatologie, Klinik und Poliklinik für Gastroenterologie und Rheumatologie, Universitätsklinikum Leipzig

Sponsor Universität Leipzig Ritterstr. 26, 04109 Leipzig

EudraCT: 2013-004882-15 DRKS: DRKS00006240

Programme: University Leipzig (Sponsor)

Public web page: Not specified

LHA - Leipzig Health Atlas

The Leipzig Health Atlas (LHA) 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 in which our team has scientific and clinical expertise.

Programme: i:DSem - Integrative Datensemantik in der Systemmedizin

Public web page: https://www.health-atlas.de

Start date: 1st Apr 2016

End date: 28th Feb 2021

Methodical Use Case PheP

PheP is a platform that enables clinical researchers to work together with statisticians and computer scientists in interdisciplinary collaboration to pursue scientific issues that previously seemed economically and technologically unthinkable. For this purpose, it is necessary to build data sets that can be used for clinical-epidemiological and health-economic issues.From phenotypes, i.e. determinable characteristics of patients, further characteristics can be derived and provided via phenotyping. ...

Programme: MII - Medical Informatics Initiative

Public web page: https://www.smith.care/en/projects/use-case-phep/

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

NFDI4Health - TA3 Services

TA3 focusses on the services, service enabling tools, and software that NFDI4Health will provide to the user community. Services and tools that will be developed or advanced during the project will be published as open source software.

Programme: NFDI - German National Research Data Infrastructure

Public web page: https://www.nfdi4health.de/en/about-us/task-areas/ta3-services.html

NFDI4Health: inactive since

NFDI4Health - the National Research Data Infrastructure for Personal Health Data - deals with data generated in clinical trials, epidemiological and public health studies. The collection and analysis of these data on health and disease status and important factors influencing it are an essential component for the development of new therapies, comprehensive care approaches and preventive measures in a modern health care system. Although these data already meet high content quality standards, they ...

Programme: NFDI - German National Research Data Infrastructure

Public web page: https://www.nfdi4health.de/en

POLAR - Polypharmacy, Drug Interactions, Risks

The aim of the project is to use methods and processes of the Medical Informatics Initiative (MII) to contribute to the detection of health risks in patients with polypharmacy. Polypharmacy occurs especially in elderly patients with multimorbidity. Polypharmacy associated with an increased risk for medication errors and drug-drug or drug-disease interactions, which either reduce or intensify the desired effect of individual active substances or lead to undesired adverse drug effects (ADE). In the ...

Programme: MII - Medical Informatics Initiative

Public web page: https://www.medizininformatik-initiative.de/en/POLAR

Management of health information systems

Aim of the project group "Management of health information systems" is to contribute to a better health care by developing new methods and tools to support the information management.

The project is also known as: MIG - Management von Informationssystemen im Gesundheitswesen

Programme: This Project is not associated with a Programme

Public web page: https://www.imise.uni-leipzig.de/en/Groups/MIG

Methodical Use Case PheP - NLP
Methodical Use Case PheP

One of the challenges of Phenotypingt is that too little clinical information is available as machine-readable data sets. Admission letters, findings and operating room reports in particular contain valuable information such as diagnoses, medications, side effects and laboratory data that can only be extracted using methods of natural language processing and semantic text analysis methods. Natural Language Processing (NLP) is used to process documents from the Hospital Information System (HIS). ...

Submitter: Frank A. Meineke

Studies: No Studies

Resources: No Resources

Methodical Use Case PheP - Pipeline
Methodical Use Case PheP

PheP is a platform that enables clinical researchers to work together with statisticians and computer scientists in interdisciplinary collaboration to pursue scientific issues that previously seemed economically and technologically unthinkable. For this purpose, it is necessary to build data sets that can be used for clinical-epidemiological and health-economic issues.

From phenotypes, i.e. determinable characteristics of patients, further characteristics can be derived and provided via phenotyping. ...

Submitter: Frank A. Meineke

Studies: No Studies

Resources: No Resources

TA3 Services
NFDI4Health - TA3 Services
No description specified

Submitter: Frank A. Meineke

Studies: No Studies

Resources: No Resources

Test Data
POLAR - Polypharmacy, Drug Interactions, Risks

Test data for POLAR and other use cases

Submitter: Frank A. Meineke

Studies: FHIR Test Data

Resources: General FHIR Test Data, POLAR, Vorhofflimmern

FHIR Test Data
POLAR - Polypharmacy, Drug Interactions, Risks

The test data

  • are freely invented by clinical experts (manually, synthetically) and have no relation to real persons
  • have been generated by a tool developed at the University of Leipzig from contributions of different expert groups out of a MS Excel format
  • are available for free use as HL7® FHIR® bundles in json format;
  • are suitable for direct transfer into a FHIR server
  • correspond as far as ...

Submitter: Frank A. Meineke

Investigation: Test Data

Resources: General FHIR Test Data, POLAR, Vorhofflimmern

Study type: Not specified

2 hidden items
Skin single-cell transcriptomics reveals a core of sebaceous gland-relevant genes shared by mice and humans.
Project Test Demonstrator

Abstract (Expand)

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has been widely applied to dissect cellular heterogeneity in normal and diseased skin. Sebaceous glands, essential skin components with established … functions in maintaining skin integrity and emerging roles in systemic energy metabolism, have been largely neglected in scRNA-seq studies. METHODS: Departing from mouse and human skin scRNA-seq datasets, we identified gene sets expressed especially in sebaceous glands with the open-source R-package oposSOM. RESULTS: The identified gene sets included sebaceous gland-typical genes as Scd3, Mgst1, Cidea, Awat2 and KRT7. Surprisingly, however, there was not a single overlap among the 100 highest, exclusively in sebaceous glands expressed transcripts in mouse and human samples. Notably, both species share a common core of only 25 transcripts, including mitochondrial and peroxisomal genes involved in fatty acid, amino acid, and glucose processing, thus highlighting the intense metabolic rate of this gland. CONCLUSIONS: This study highlights intrinsic differences in sebaceous lipid synthesis between mice and humans, and indicates an important role for peroxisomal processes in this context. Our data also provides attractive starting points for experimentally addressing novel candidates regulating sebaceous gland homeostasis.

Authors: T. Thalheim, M. R. Schneider

Date Published: 3rd Feb 2024

Publication Type: Journal article

"fhircrackr": An R Package Unlocking Fast Healthcare Interoperability Resources for Statistical Analysis.
POLAR - Polypharmacy, Drug Interactions, Risks

Abstract (Expand)

BACKGROUND: The growing interest in the secondary use of electronic health record (EHR) data has increased the number of new data integration and data sharing infrastructures. The present work has been … developed in the context of the German Medical Informatics Initiative, where 29 university hospitals agreed to the usage of the Health Level Seven Fast Healthcare Interoperability Resources (FHIR) standard for their newly established data integration centers. This standard is optimized to describe and exchange medical data but less suitable for standard statistical analysis which mostly requires tabular data formats. OBJECTIVES: The objective of this work is to establish a tool that makes FHIR data accessible for standard statistical analysis by providing means to retrieve and transform data from a FHIR server. The tool should be implemented in a programming environment known to most data analysts and offer functions with variable degrees of flexibility and automation catering to users with different levels of FHIR expertise. METHODS: We propose the fhircrackr framework, which allows downloading and flattening FHIR resources for data analysis. The framework supports different download and authentication protocols and gives the user full control over the data that is extracted from the FHIR resources and transformed into tables. We implemented it using the programming language R [1] and published it under the GPL-3 open source license. RESULTS: The framework was successfully applied to both publicly available test data and real-world data from several ongoing studies. While the processing of larger real-world data sets puts a considerable burden on computation time and memory consumption, those challenges can be attenuated with a number of suitable measures like parallelization and temporary storage mechanisms. CONCLUSION: The fhircrackr R package provides an open source solution within an environment that is familiar to most data scientists and helps overcome the practical challenges that still hamper the usage of EHR data for research.

Authors: J. Palm, F. A. Meineke, J. Przybilla, T. Peschel

Date Published: 25th Jan 2023

Publication Type: Journal article

The Leipzig Health Atlas-An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online.
LHA - Leipzig Health Atlas

Abstract (Expand)

BACKGROUND: Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research … domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains. OBJECTIVE: The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects. METHODS: Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups. RESULTS: The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

Authors: T. Kirsten, F. A. Meineke, H. Loeffler-Wirth, C. Beger, A. Uciteli, S. Staubert, M. Lobe, R. Hansel, F. G. Rauscher, J. Schuster, T. Peschel, H. Herre, J. Wagner, S. Zachariae, C. Engel, M. Scholz, E. Rahm, H. Binder, M. Loeffler

Date Published: 3rd Aug 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

Ontological representation, classification and data-driven computing of phenotypes.
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and … epidemiological studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term 'phenotype' has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimisation. In the context of a methodological use case 'phenotype pipeline' (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. RESULTS: In this article, we present a Core Ontology of Phenotypes (COP) and the software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model, classify and compute phenotypes from already available data. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated with selected phenotypes including SOFA score, socio-economic status, body surface area and WHO BMI classification based on available medical data. CONCLUSIONS: We developed a novel ontology-based method to model phenotypes of living beings with the aim of automated phenotype reasoning based on available data. This new approach can be used in clinical context, e.g., for supporting the diagnostic process, evaluating risk factors, and recruiting appropriate participants for clinical and epidemiological studies.

Authors: A. Uciteli, C. Beger, T. Kirsten, F. A. Meineke, H. Herre

Date Published: 21st Dec 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: M. Lobe, F. Matthies, S. Staubert, F. A. Meineke, A. Winter

Date Published: 16th Jun 2020

Publication Type: Journal article

Ontological Modelling and Reasoning of Phenotypes
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological … studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term ‘phenotype’ has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimization. In the context of a methodological use case “phenotype pipeline” (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. In this article we present a Core Ontology of Phenotypes (COP) and a software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model and calculate phenotypes. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated based on different phenotypes (including SOFA score, socioeconomic status, body surface area and WHO BMI classification) and several data sets.

Authors: Alexandr Uciteli, Christoph Beger, Toralf Kirsten, Frank A. Meineke, Heinrich Herre

Date Published: 20th Dec 2019

Publication Type: InProceedings

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

2 hidden items
Local Data Hub - ein Service der NFDI4Health
NFDI4Health - TA3 Services

Der Local Data Hub (LDH) dient der Präsentation und dem Austausch Ihrer Projekte, Studien, Publikationen, (bio-)medizinischen Daten, Modelle und Softwaretools aus dem Bereich der Gesundheitsforschung und basiert auf den FAIR-Prinzipien (Findable, Accessible,Interoperable, Reusable). Zielgruppen sind Forscher:innen aus den Fachbereichen (Bio)Medizin, Epidemiologie, Biostatistik, Modellierung oder Bio- und Medizininformatik. Der LDH ist eine einfach zu verwaltende, webbasierte Softwarelösung, die ...

Creator: Frank A. Meineke

Submitter: Frank A. Meineke

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Abstract: The Leipzig Health Atlas – A Repository for Research Data and Models
LHA - Leipzig Health Atlas

The publication of research results is part of good scientific practice and is increasingly ex-pected and demanded. The FAIR data principles of data sharing are an important guideline - even if medical data sharing makes it necessary to define access restrictions.

Creators: René Hänsel, Frank A. Meineke, Christoph Beger

Submitter: Christoph Beger

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Poster: The Leipzig Health Atlas - A Repository for Research Data and Models
LHA - Leipzig Health Atlas

The Leipzig Health Atlas (LHA) offers a platform for presentation and exchange of publications, (bio-) medical data, models and software tools from the field of health research. The LHA is based on the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable). Currently, more than 18 research consortia contribute data from the domains lymphoma, glioma, sepsis, hereditary colorectal and breast cancer, and others. Target groups are clinicians, epidemiologists, molecular geneticists, human ...

Creators: René Hänsel, Frank A. Meineke, Christoph Beger

Submitter: Christoph Beger

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University Leipzig (Sponsor)
No description specified

Projects: AbCD, GRAFT, TIBICO, STOP-NUC, BASALIT, ADIPO-VENT

Web page: Not specified

i:DSem - Integrative Datensemantik in der Systemmedizin

Within the framework of the funding measure "i:DSem - Integrative Data Semantics in Systems Medicine", the Federal Ministry of Education and Research supports research projects that take up this approach. Interdisciplinary research projects are to create the basis so that in the future, for example, the attending physician will have application-oriented computer programmes at his or her disposal that will enable him or her to access all clinically relevant data. This should significantly support ...

Projects: LHA - Leipzig Health Atlas

Web page: https://www.gesundheitsforschung-bmbf.de/de/i-dsem-integrative-datensemantik-in-der-systemmedizin-3367.php

NFDI - German National Research Data Infrastructure

In the German National Research Data Infrastructure (NFDI), valuable data from science and research are systematically accessed, networked and made usable in a sustainable and qualitative manner for the entire German science system. Up to now, they have mostly been available on a decentralised, project-related or temporary basis. The NFDI aims to create a permanent digital repository of knowledge as an indispensable prerequisite for new research questions, findings and innovations. Relevant data ...

Projects: NFDI4Health, Task Force COVID-19 Leipzig, NFDI4Health - TA3 Services, Clinical Trials Leipzig

Web page: https://www.nfdi.de/?lang=en

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

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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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