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The Onto-Med Research Group conducts basic research in formal ontology, designs formal tools for constructing and managing ontologies and develops top level ontologies as well as domain and core ontologies for medicine, bio-medicine and biology, but also for other fields. The Onto-Med group uses an interdisciplinary approach, combining methods from logic, computer science, philosophy and cognitive linguistics. The Onto-Med group considers Formal Ontology as an evolving science which is concerned with systematically developing axiomatic theories that describe forms, structures, and modes of being at different levels of abstraction and granularity. The roots of formal ontology can be traced back to the philosophical investigations of Aristotle and Plato. Their work was creatively enriched during the early Middle Ages by Islamic philosophers, including Avicenna, renowned as one of the history's greatest thinkers and medical scholars. The Onto-Med Research Group was founded in 2002 and is a result of a collaboration between the Institute for Medical Informatics, Statistics, and Epidemiology (IMISE), University of Leipzig, and the Department of Formal Concepts at the Institute for Informatics (IfI), University of Leipzig.
Programme: This Project is not associated with a Programme
Health Atlas ID: 7Q0CTG2M1H-2
Public web page: http://www.onto-med.de
Organisms: No Organisms specified
Human Diseases: No Human Disease specified
Health Atlas PALs: Heinrich Herre
Project Coordinators: No Project coordinators for this Project
Project start date: 1st Jan 2002
Related items
- Institutions (1)
- Investigations (1)
- Studies (3)
- Resources (3)
- Publications (3)
- Data files (13+2)
- Models (2)
- Presentations (1)
- People (3)
Snapshots: No snapshots
Studies: Ontological Modelling of Basic Eligibility Criteria, Ontological Modelling of Type 2 Diabetes Mellitus (T2DM) Phenotype, PhenoMan Evaluation with Synthetic FHIR Data
Resources: Basic Eligibility Criteria of an Example Blood Pressure Study, Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan), PhenoMan Evaluation - Synthetic FHIR Data
We evaluated if the PhenoMan returns correct/complete result sets and if it is working with real data. To simulate a FHIR health data store with real data we used Synthea(TM) to generate a large data set and imported it into a HAPI FHIR JPA Server. Based on the synthetic data set we developed ten example queries with different structure and complexity with PhenoMan and SQL. We compared the results of the queries in means of execution time and equality of results.
The detailed steps of the evaluation
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Investigation: Ontology-based Phenotyping
Resources: PhenoMan Evaluation - Synthetic FHIR Data
Investigation: Ontology-based Phenotyping
Resources: Basic Eligibility Criteria of an Example Blood Pressure Study
Investigation: Ontology-based Phenotyping
Resources: Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan)
This assay bundles all synthetic FHIR data of the PhenoMan evaluation. The data arised from a subset of a Synthea(TM) generated data set.
We truncated some resource types like Encounter and Provider to reduce the size of the data set and to speed up the import in a FHIR health data store.
Submitter: Christoph Beger
Resource type: Result Dataset of Clinical Study
Technology type: Technology Type
Snapshots: No snapshots
Investigation: Ontology-based Phenotyping
Study: PhenoMan Evaluation with Synthetic FHIR Data
Organisms: No organisms
Human Diseases: asthma, bronchial disease, hypertension, obesity
SOPs: No SOPs
Data files: PhenoMan Evaluation - AllergyIntolerance FHIR R..., PhenoMan Evaluation - Condition FHIR Resources, PhenoMan Evaluation - Observation FHIR Resources, PhenoMan Evaluation - Patient FHIR Resources
Submitter: Alexandr Uciteli
Biological problem addressed: Model Analysis Type
Snapshots: No snapshots
Investigation: Ontology-based Phenotyping
Study: Ontological Modelling of Basic Eligibility Crit...
Organisms: No organisms
Human Diseases: No human diseases
Models: No Models
SOPs: No SOPs
Data files: Eligibility Criteria Ontology for an Example Bl...
We modelled the algorithm for determining Type 2 Diabetes Mellitus (T2DM) cases presented by PheKB.org using Phenotype Manager (PhenoMan).
Submitter: Alexandr Uciteli
Biological problem addressed: Model Analysis Type
Snapshots: No snapshots
Investigation: Ontology-based Phenotyping
Study: Ontological Modelling of Type 2 Diabetes Mellit...
Organisms: No organisms
Human Diseases: diabetes mellitus
Models: No Models
SOPs: No SOPs
Data files: T2DM Case 1 Reasoner Report, T2DM Case 2 Reasoner Report, T2DM Case 3 Reasoner Report, T2DM Case 4 Reasoner Report, T2DM Case 5 Reasoner Report, T2DM Graphical Representation, T2DM Ontology, T2DM Tabular Representation
Abstract (Expand)
Authors: Alexandr Uciteli, Christoph Beger, Toralf Kirsten, Frank A. Meineke, Heinrich Herre
Date Published: 20th Dec 2019
Publication Type: InProceedings
Citation: CEUR Workshop Proceedings. 2019 Sep;2570. issn: 1613-0073.
Abstract (Expand)
Authors: A. Uciteli, C. Beger, C. Rillich, F. A. Meineke, M. Loffler, H. Herre
Date Published: 2018
Publication Type: InBook
DOI: 10.1007/978-3-662-55433-3_9
Citation: Semantic Applications,pp.111-123,Springer Berlin Heidelberg
Abstract (Expand)
Authors: C. Beger, A. Uciteli, H. Herre
Date Published: 9th Sep 2017
Publication Type: Journal article
PubMed ID: 28883194
Citation: Stud Health Technol Inform. 2017;243:170-174.
T2DM Phenotype Algorithm Specification Ontology (PASO) developed using PhenoMan
Investigations: Ontology-based Phenotyping
Studies: Ontological Modelling of Type 2 Diabetes Mellit...
Resources: Ontological Modelling of T2DM Phenotype using P...
The tabular representation of the T2DM phenotype algorithm generated by PhenoMan using the T2DM ontology
Investigations: Ontology-based Phenotyping
Studies: Ontological Modelling of Type 2 Diabetes Mellit...
Resources: Ontological Modelling of T2DM Phenotype using P...
This data file contains FHIR bundles of observation resources, which were used for the evaluation of the PhenoMan.
Originally the observation data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.
Please import the patient resources prior to the observations.
This data file contains 8,026,380 observations.
Creators: Alexandr Uciteli, Christoph Beger
Submitter: Christoph Beger
Data file type: Clinical Data
Human Diseases: obesity, bronchial disease, asthma, hypertension
Investigations: Ontology-based Phenotyping
Studies: PhenoMan Evaluation with Synthetic FHIR Data
Resources: PhenoMan Evaluation - Synthetic FHIR Data
This data file contains FHIR bundles of patient resources, which were used for the evaluation of the PhenoMan.
Originally the patient data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.
This data file contains 66,018 patients.
Creators: Alexandr Uciteli, Christoph Beger
Submitter: Christoph Beger
Data file type: Clinical Data
Human Diseases: obesity, bronchial disease, asthma, hypertension
Investigations: Ontology-based Phenotyping
Studies: PhenoMan Evaluation with Synthetic FHIR Data
Resources: PhenoMan Evaluation - Synthetic FHIR Data
This data file contains FHIR bundles of allergy intolerance resources, which were used for the evaluation of the PhenoMan.
Originally the allergy intolerance data were generated with Synthea(TM) and truncated to reduce overall size and import times into a HAPI FHIR JPA Server.
Please import the patient resources prior to the allergy intolerances.
This data file contains 563 allergy intolerances.
Creators: Alexandr Uciteli, Christoph Beger
Submitter: Christoph Beger
Data file type: Clinical Data
Human Diseases: obesity, bronchial disease, asthma, hypertension
Investigations: Ontology-based Phenotyping
Studies: PhenoMan Evaluation with Synthetic FHIR Data
Resources: PhenoMan Evaluation - Synthetic FHIR Data
Core Ontology of Phenotypes. Contribute to Onto-Med/COP development by creating an account on GitHub.
Creators: Heinrich Herre, Alexandr Uciteli, Christoph Beger
Submitter: Christoph Beger
Model type: Not specified
Model format: Not specified
Environment: Not specified
Organism: Not specified
Human Disease: Not specified
Investigations: No Investigations
Studies: No Studies
Resources: No Resources
This is a Drupal 8 Module to import nodes and taxonomies into Drupal, using the available API. The module is capable of importing a JSON or OWL file. Idea is to enable users to upload a file containing all information about nodes and their relations. The module will then import all contained information with the Drupal 8 API. Nodes can be specified as "articles" or any other custom node type. The node classification becomes one (or multiple) hierachical vocabulary. Supported import formats are
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Creator: Christoph Beger
Submitter: Christoph Beger
Model type: Not specified
Model format: Not specified
Environment: Not specified
Organism: Not specified
Human Disease: Not specified
Investigations: No Investigations
Studies: No Studies
Resources: No Resources
Presentation on JOWO/ODLS 2019 in Graz
Creators: Alexandr Uciteli, Christoph Beger
Submitter: Christoph Beger
Projects: Onto-Med Research Group
Institutions: Institute for Medical Informatics, Statistics and Epidemiology