TY - JOUR
T1 - Ontology-based temporal analysis for medical device adverse event- A use case study on Late Stent Thrombosis
AU - Clark, Kim
AU - Sharma, Deepak
AU - Qin, Rui
AU - Jiang, Guoqian
AU - Chute, Christopher G.
AU - Tao, Cui
PY - 2013
Y1 - 2013
N2 - 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) for automatically identifying, ordering, and calculating the duration of temporal events within adverse event report narratives. The Objective of this research is to evaluate the feasibility of the CNTRO Timeline Library using a real clinical use case application (late stent thrombosis adverse events). Narratives from late stent thrombosis adverse events documented within the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database were used as a test case. 238 annotated narratives were evaluated using the CNTRO Timeline Library. The CNTRO Timeline Library had a 95.38% accuracy in correctly ordering events within the narratives. The duration function of the CNTRO Timeline Library was also evaluated and found to have 80% accuracy in correctly determining the duration of an event across 41 narratives, and 76.6% accuracy in determining the duration between two given events across 77 narratives. Within this paper is an example of how the durations calculated by the CNTRO Timeline Library can be used to examine therapeutic guidelines. Complaint narratives were separated into two groups based on a long (greater than 6 months) or short (6 months or less) duration of antiplatelet therapy administration. The duration of antiplatelet administration was then compared to the duration between stent implantation and occurrence of late stent thrombosis. The goal of this analysis was to show how the CNTRO ontology and is associated Timeline Library could be used to examine recommendations for length of drug administration. In this use case, the result supports guidance for use of longer antiplatelet therapy. This example validates the CNTRO System's ability to confirm known temporal trends.
AB - 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) for automatically identifying, ordering, and calculating the duration of temporal events within adverse event report narratives. The Objective of this research is to evaluate the feasibility of the CNTRO Timeline Library using a real clinical use case application (late stent thrombosis adverse events). Narratives from late stent thrombosis adverse events documented within the Food and Drug Administration's (FDA) Manufacturing and User Facility Device Experience (MAUDE) database were used as a test case. 238 annotated narratives were evaluated using the CNTRO Timeline Library. The CNTRO Timeline Library had a 95.38% accuracy in correctly ordering events within the narratives. The duration function of the CNTRO Timeline Library was also evaluated and found to have 80% accuracy in correctly determining the duration of an event across 41 narratives, and 76.6% accuracy in determining the duration between two given events across 77 narratives. Within this paper is an example of how the durations calculated by the CNTRO Timeline Library can be used to examine therapeutic guidelines. Complaint narratives were separated into two groups based on a long (greater than 6 months) or short (6 months or less) duration of antiplatelet therapy administration. The duration of antiplatelet administration was then compared to the duration between stent implantation and occurrence of late stent thrombosis. The goal of this analysis was to show how the CNTRO ontology and is associated Timeline Library could be used to examine recommendations for length of drug administration. In this use case, the result supports guidance for use of longer antiplatelet therapy. This example validates the CNTRO System's ability to confirm known temporal trends.
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M3 - Conference article
AN - SCOPUS:84908327737
SN - 1613-0073
VL - 1114
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 6th International Workshop on Semantic Web Applications and Tools for Life Sciences, SWAT4LS 2013
Y2 - 10 December 2013 through 10 December 2013
ER -