Published January 2023 | Version v1
Project deliverable Open

D4.1 Annotation guidelines

  • 1. ROR icon Medical University of Graz
  • 2. ROR icon Averbis (Germany)
  • 3. ROR icon North Estonia Medical Centre
  • 4. B!Loba


Manual annotations of clinical narratives are crucial for the adoption and evaluation of NLP tools, which support an overall AI assisted data curation approach within the AIDAVA project. In the preparation phase - in scope of this deliverable - for the Task “T4.3 Manual Annotation of text documents in 3 languages”, and based on the data elements identified for the use cases cross border breast cancer patient registries, and longitudinal individual health records for patients at risk of sudden cardiac arrest, requirements for the manual annotation tool have been formulated. Grounded on the requirement analysis, INCEpTION was chosen to support the manual annotation task. A first manual annotation schema was developed and tested, with a focus on the use of SNOMED CT and FHIR for the normalized form of the entity types of interest. A first version of the annotation guidelines is drafted in this document and will be revised in close cooperation with the manual annotators at the three different clinical sides (Med Uni Graz with MUG, Northern Estonian Medical Center with NEMC, Maastricht Medical University Center with UM), AVER and ONTO during the piloting phase until Q1 2023.


AIDAVA_101057062_D_4_1_ Annotation guidelines_Final_zenodo.pdf

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AIDAVA - AI powered Data Curation & Publishing Virtual Assistant 101057062
European Commission