A use case study on late stent thrombosis for ontology-based temporal reasoning and analysis

Kim Clark, Deepak Sharma, Rui Qin, Christopher G. Chute, Cui Tao

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In this paper, we show how we have applied the Clinical Narrative Temporal Relation Ontology (CNTRO) and its associated temporal reasoning system (the CNTRO Timeline Library) to trend temporal information within medical device adverse event report narratives. 238 narratives documenting occurrences of late stent thrombosis adverse events from the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database were annotated and evaluated using the CNTRO Timeline Library to identify, order, and calculate the duration of temporal events. The CNTRO Timeline Library had a 95% accuracy in correctly ordering events within the 238 narratives. 41 narratives included an event in which the duration was documented, and the CNTRO Timeline Library had an 80% accuracy in correctly determining these durations. 77 narratives included documentation of a duration between events, and the CNTRO Timeline Library had a 76% accuracy in determining these durations. This paper also includes an example of how this temporal output from the CNTRO ontology can be used to verify recommendations for length of drug administration, and proposes that these same tools could be applied to other medical device adverse event narratives in order to identify currently unknown temporal trends.

Original languageEnglish (US)
Article number49
JournalJournal of Biomedical Semantics
Issue number1
StatePublished - Dec 11 2014
Externally publishedYes

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Health Informatics
  • Computer Networks and Communications


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