Filter and export

Publications

6 Publications matching the given criteria: (Clear all filters)
Project: Onto-Med Research Group6
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

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

Ontology-Based Modelling of Web Content: Example Leipzig Health Atlas
Onto-Med Research Group

Abstract (Expand)

The realisation of a complex web portal, including the modelling of content, is a challenging process. The contents describe different interconnected entities that form a complex structure. The entities … and their relations have to be systematically analysed, and the content has to be specified and integrated into a content management system (CMS). Ontologies provide a suitable solution for modelling and specifying complex entities and their relations. However, the functionality for automated import of ontologies is not available in current content management systems. In order to describe the content of a web portal, we developed an ontology. Based on this ontology, we implemented a pipeline that allows the specification of the portal’s content and its import into the CMS Drupal. Our method is generic. It enables the development of web portals with the focus on a suitable representation of structured knowledge (entities, their properties and relations). Furthermore, it makes it possible to represent existing ontologies in such a way that their content can be understood by users without knowledge of ontologies and their semantics. Our approach has successfully been applied in building the LHA (Leipzig Health Atlas) portal, which provides access to metadata, data, publications and methods from various research projects at the University of Leipzig.

Authors: A. Uciteli, C. Beger, C. Rillich, F. A. Meineke, M. Loffler, H. Herre

Date Published: 2018

Publication Type: InBook

Light-Weighted Automatic Import of Standardized Ontologies into the Content Management System Drupal.
Onto-Med Research Group

Abstract (Expand)

The amount of ontologies, which are utilizable for widespread domains, is growing steadily. BioPortal alone, embraces over 500 published ontologies with nearly 8 million classes. In contrast, the vast … informative content of these ontologies is only directly intelligible by experts. To overcome this deficiency it could be possible to represent ontologies as web portals, which does not require knowledge about ontologies and their semantics, but still carries as much information as possible to the end-user. Furthermore, the conception of a complex web portal is a sophisticated process. Many entities must be analyzed and linked to existing terminologies. Ontologies are a decent solution for gathering and storing this complex data and dependencies. Hence, automated imports of ontologies into web portals could support both mentioned scenarios. The Content Management System (CMS) Drupal 8 is one of many solutions to develop web presentations with less required knowledge about programming languages and it is suitable to represent ontological entities. We developed the Drupal Upper Ontology (DUO), which models concepts of Drupal's architecture, such as nodes, vocabularies and links. DUO can be imported into ontologies to map their entities to Drupal's concepts. Because of Drupal's lack of import capabilities, we implemented the Simple Ontology Loader in Drupal (SOLID), a Drupal 8 module, which allows Drupal administrators to import ontologies based on DUO. Our module generates content in Drupal from existing ontologies and makes it accessible by the general public. Moreover Drupal offers a tagging system which may be amplified with multiple standardized and established terminologies by importing them with SOLID. Our Drupal module shows that ontologies can be used to model content of a CMS and vice versa CMS are suitable to represent ontologies in a user-friendly way. Ontological entities are presented to the user as discrete pages with all appropriate properties, links and tags.

Authors: C. Beger, A. Uciteli, H. Herre

Date Published: 9th Sep 2017

Publication Type: Journal article

Navigate

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.

Registered Repository

re3data.org Badge
Powered by
 (v.1.13.0-master)
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