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OMIM mapping confirmed by DO. [SN].
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This population-based study examined 10,000 participants randomly selected from the Leipzig population (2011 to 2014). A follow-up is to be carried out from 2017 - 2020. The study mainly included people aged between 40 and 79. All participants underwent a 6-hour study program and people over 60 years of age were invited two more times to in-depth study of cognition and depression and the brain (MRI, EEG). Extensive measurements of genome, metabolome and transcriptome are available. The LIFE-ADULT
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Programme: Epidemiology
Public web page: http://life.uni-leipzig.de/en/adults/life_adult.html
Start date: 1st Jan 2009
Organisms: Homo sapiens
Human Diseases: mood disorder, dementia, coronary artery disease, obesity
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
Abstract (Expand)
Authors: H. Loeffler-Wirth, M. Vogel, T. Kirsten, F. Glock, T. Poulain, A. Korner, M. Loeffler, W. Kiess, H. Binder
PubMed ID: 30212520
Citation: PLoS One. 2018 Sep 13;13(9):e0203628. doi: 10.1371/journal.pone.0203628. eCollection 2018.
Abstract (Expand)
Authors: K. Hohloch, B. Altmann, M. Pfreundschuh, M. Loeffler, N. Schmitz, F. Zettl, M. Ziepert, L. Trumper
Date Published: 2nd Dec 2017
Publication Type: Not specified
Human Diseases: obesity, B-cell lymphoma
PubMed ID: 29193018
Citation: Br J Haematol. 2018 Jan;180(2):236-245. doi: 10.1111/bjh.15029. Epub 2017 Nov 28.
Abstract (Expand)
Authors: H. Loeffler-Wirth, M. Vogel, T. Kirsten, F. Glock, T. Poulain, A. Korner, M. Loeffler, W. Kiess, H. Binder
PubMed ID: 29053732
Citation: PLoS One. 2017 Oct 20;12(10):e0186881. doi: 10.1371/journal.pone.0186881. eCollection 2017.
Abstract (Expand)
Authors: F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, T. Luck, S. G. Riedel-Heller, M. Loeffler, M. L. Schroeter, M. Stumvoll, A. Villringer, A. V. Witte
PubMed ID: 28397392
Citation: Hum Brain Mapp. 2017 Jul;38(7):3502-3515. doi: 10.1002/hbm.23605. Epub 2017 Apr 11.
Abstract (Expand)
Authors: M. Keller, L. Hopp, X. Liu, T. Wohland, K. Rohde, R. Cancello, M. Klos, K. Bacos, M. Kern, F. Eichelmann, A. Dietrich, M. R. Schon, D. Gartner, T. Lohmann, M. Dressler, M. Stumvoll, P. Kovacs, A. M. DiBlasio, C. Ling, H. Binder, M. Bluher, Y. Bottcher
PubMed ID: 28123940
Citation: Mol Metab. 2016 Nov 16;6(1):86-100. doi: 10.1016/j.molmet.2016.11.003. eCollection 2017 Jan.
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
This data file contains FHIR bundles of condition resources, which were used for the evaluation of the PhenoMan.
Originally the condition 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 conditions.
This data file contains 139,763 conditions.
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
Emerging health geography research analyzes and visualizes health behaviors and outcomes in relation to urban environmental data and related official statistics to produce “health reports” for specific areas. This can be extended to developments in urban planning, e.g., to identify districts or neighborhoods for social investments or restrictions.
We mapped anthropometric data the large LIFE Adult population (10,000 participants) onto the Leipzig map. In particular, we derived the body mass index
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Creator: Ying-Chi Lin
Submitter: René Hänsel
Model type: Not specified
Model format: Not specified
Environment: Not specified
Organism: Not specified
Human Disease: obesity
Investigations: No Investigations
Studies: No Studies
Resources: No Resources