2019
DOI: 10.1186/s12911-019-0807-y
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Using the distance between sets of hierarchical taxonomic clinical concepts to measure patient similarity

Abstract: Background Many clinical concepts are standardized under a categorical and hierarchical taxonomy such as ICD-10, ATC, etc. These taxonomic clinical concepts provide insight into semantic meaning and similarity among clinical concepts and have been applied to patient similarity measures. However, the effects of diverse set sizes of taxonomic clinical concepts contributing to similarity at the patient level have not been well studied. Methods In this paper the most widely… Show more

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Cited by 36 publications
(34 citation statements)
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“…Inter-rater reliability for abstracting clinical cases into UMLS codes or SNOMED CT codes is another concern [6-7]. Finally, we have not compared the semantic weighted bipartite distance metric to other available distance metrics [12,27]. Additional work will need to be done to establish the reliability of the abstraction process and identify the best metrics to calculate patient distances between neurological patients.…”
Section: Discussionmentioning
confidence: 99%
“…Inter-rater reliability for abstracting clinical cases into UMLS codes or SNOMED CT codes is another concern [6-7]. Finally, we have not compared the semantic weighted bipartite distance metric to other available distance metrics [12,27]. Additional work will need to be done to establish the reliability of the abstraction process and identify the best metrics to calculate patient distances between neurological patients.…”
Section: Discussionmentioning
confidence: 99%
“…This is known as post-coordination [15]. Concept ontologies that are organized hierarchically support the calculation of inter-concept distances [16][17][18][19][20][21][22][23][24].…”
Section: The Ontology Should Be Organized Hierarchicallymentioning
confidence: 99%
“…Some somewhat arbitrary subsumption decisions may influence how accurately the concept distance measures derived from a concept hierarchy align with expert opinion. Considerable effort has been devoted to finding the best distance metrics for concept hierarchies that give the closest results to expert opinion [19,20,22]. However, when the hierarchy itself is not aligned with expert opinion, the choice of distance metric may be less critical.…”
Section: Curation Of the Hierarchymentioning
confidence: 99%
“…Mabotuwana et al found that semantic augmentation of inter-document distances increased the separation between the centroid of the head CT scan reports and the centroid of the abdomen CT reports. Jia et al [14] examined the ability of patient distances generated by ICD-10 diagnoses to predict hospital length of stay.…”
Section: Distance Metricsmentioning
confidence: 99%