Arguello, M, Lekkas, S, Des, J, Fernandez Prieto, MJ and Mikhailov, L 2014, 'Combining semantic web technologies with evolving fuzzy classifier eClass for EHR-based phenotyping : a feasibility study' , in: Research and Development in Intelligent Systems XXXI : Incorporating Applications and Innovations in Intelligent Systems XXII , Research and Development in Intelligent Systems, XIV (XXXI) , Springer International Publishing, Switzerland, pp. 195-208.
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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 1956 clinical statements from EHRs. The evaluation performed with clinicians demonstrates the feasibility and practical acceptability of the approach proposed.
| Item Type: | Book Section |
|---|---|
| Editors: | Bramer, M and Petridis, M |
| Additional Information: | Best Refereed Paper in Application Stream. |
| Themes: | Health and Wellbeing |
| Schools: | Schools > School of Humanities, Languages & Social Sciences > Centre for Linguistics and Applied Linguistics |
| Publisher: | Springer International Publishing |
| Refereed: | Yes |
| Series Name: | Research and Development in Intelligent Systems |
| ISBN: | 9783319120690 |
| Related URLs: | |
| Funders: | Non funded research |
| Depositing User: | MJ Fernandez-Prieto |
| Date Deposited: | 17 Jun 2015 15:27 |
| Last Modified: | 16 Feb 2022 16:47 |
| URI: | https://usir.salford.ac.uk/id/eprint/35263 |
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