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Erschienen in:
On Ontological Expressivity and Modelling Argumentation Schemes Using COGUI Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

Combining Semantic Web Technologies with Evolving Fuzzy Classifier eClass for EHR-Based Phenotyping: A Feasibility Study

verfasst von : M. Arguello, S. Lekkas, J. Des, M.J. Fernandez-Prieto, L. Mikhailov

Erschienen in: Research and Development in Intelligent Systems XXXI

Verlag: Springer International Publishing

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Abstract

In parallel to nation-wide efforts for setting up shared electronic health records (EHRs) across healthcare settings, several large-scale national and international projects are developing, validating, and deploying electronic EHR-oriented phenotype algorithms that aim at large-scale use of EHRs data for genomic studies. A current bottleneck in using EHRs data for obtaining computable phenotypes is to transform the raw EHR data into clinically relevant features. The research study presented here proposes a novel combination of Semantic Web technologies with the on-line evolving fuzzy classifier eClass to obtain and validate EHR-driven computable phenotypes derived from 1,956 clinical statements from EHRs. The evaluation performed with clinicians demonstrates the feasibility and practical acceptability of the approach proposed.

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Metadaten
Titel
Combining Semantic Web Technologies with Evolving Fuzzy Classifier eClass for EHR-Based Phenotyping: A Feasibility Study
verfasst von
M. Arguello
S. Lekkas
J. Des
M.J. Fernandez-Prieto
L. Mikhailov
Copyright-Jahr
2014
Buch
Research and Development in Intelligent Systems XXXI

Print ISBN: 978-3-319-12068-3

Electronic ISBN: 978-3-319-12069-0

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-12069-0_15