Evaluating semantic similarity methods for comparison of text-derived phenotype profiles

Evaluating semantic similarity methods for comparison of text-derived phenotype profiles

Abstract Background Semantic similarity is a valuable tool for analysis in biomedicine. When applied to phenotype profiles derived from clinical text, they have the capacity to enable and enhance ‘patient-like me’ analyses, automated coding, differential diagnosis, and outcome prediction. While a la...

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Bibliographic Details
Main Authors: Luke T. Slater, Sophie Russell, Silver Makepeace, Alexander Carberry, Andreas Karwath, John A. Williams, Hilary Fanning, Simon Ball, Robert Hoehndorf, Georgios V. Gkoutos
Format: Article
Language:English
Published: BMC 2022-02-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Semantic web
Ontology
Differential diagnosis
MIMIC-III
Semantic similarity
Online Access:https://doi.org/10.1186/s12911-022-01770-4

Internet

https://doi.org/10.1186/s12911-022-01770-4

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