Terminology and Ontology Development for Semantic Annotation: A Use Case on Sepsis and Adverse Events

Tracking #: 3226-4440

Authors: 
Melissa Yan
Lise Tuset Gustad
Lise Husby Høvik1
Øystein Nytrø

Responsible editor: 
Guest Editors SW Meets Health Data Management 2022

Submission type: 
Full Paper
Abstract: 
Annotations enrich text corpora and provide necessary labels for natural language processing studies. To reason and infer underlying implicit knowledge captured by labels, an ontology is needed to provide a semantically annotated corpus with structured domain knowledge. Utilizing a corpus of adverse event documents annotated for sepsis-related signs and symptoms as a use case, this paper details how a terminology and corresponding ontology were developed. The Annotated Adverse Event NOte TErminology (AAENOTE) represents annotated documents and assists annotators in annotating text. In contrast, the complementary Catheter Infection Indications Ontology (CIIO) is intended for clinician use and captures domain knowledge needed to reason and infer implicit information from data. The approach taken makes ontology development understandable and accessible to domain experts without formal ontology training.
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Decision/Status: 
Accept

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Review #1
Anonymous submitted on 27/Oct/2022
Suggestion:
Accept
Review Comment:

I appreciate the additional work done by the authors to improve this work. Almost all of my points were addressed.
I believe that overall the current version is acceptable for publication.

Review #2
Anonymous submitted on 31/Oct/2022
Suggestion:
Accept
Review Comment:

I would like to thanks the authors for handling my comments in great details.
I am satisfied with the revised version.