Methodical Use Case PheP - NLP
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). The process is academically led by the Jena University Language & Information Engineering Lab (JULIE Lab) in collaboration with leading companies in the field of language processing.
LHA ID: 8GAE975JF4-7
Projects: Methodical Use Case PheP
Investigation position:
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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/
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
Abstract (Expand)
Authors: U. Hahn, F. Matthies, C. Lohr, Markus Löffler
Date Published: 24th Apr 2018
Publication Type: InProceedings
Projects: SMITH - Smart Medical Information Technology for Healthcare
Institutions: Friedrich-Schiller-Universität Jena
- since 2023: Research Assistant at IMISE of Leipzig University
- 2016 - 2022: Research Assistant at JULIE Lab of Friedrich Schiller University Jena
- 2015 - 2016: Research Assistant at Chemnitz University of Technology, Chair Media Informatics and Chair Practical Computer Science
- 2007 - 2015: Student Assistant at Klinikum Chemnitz (Klinik für Allgemein- und Viszeralchirurgie)
- 2012 - 2015: Studies of Computer Science at Chemnitz University of Technology (Master of Science)
- 2007 - 2012: ...
Profile image source: Swen Reichhold
Projects: LHA - Leipzig Health Atlas, SMITH - Smart Medical Information Technology for Healthcare, POLAR - Polypharmacy, Drug Interactions, Risks, Management of health information systems, Project Test Demonstrator, NFDI4Health - TA3 Services, NFDI4Health, Methodical Use Case PheP, STOP-NUC, BASALIT
Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
https://orcid.org/0000-0002-9256-7543
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
