Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0036759
Title: Center of excellence in research reporting in neurosurgery - diagnostic ontology
Authors: Zaveri A.
Shah J.
Pradhan S.
Rodrigues C.
Barros J.
Ang B.T. 
Pietrobon R.
Keywords: article
clinical research
diagnostic accuracy
diagnostic computational ontology
diagnostic test
evidence based medicine
information processing
information retrieval
internal consistency
mathematical analysis
medical literature
neurosurgery
observer variation
online system
randomized controlled trial (topic)
research reporting
standardization
systematic review (topic)
validation study
Biomedical Research
Evidence-Based Medicine
Humans
Neurosurgery
Issue Date: 2012
Citation: Zaveri A., Shah J., Pradhan S., Rodrigues C., Barros J., Ang B.T., Pietrobon R. (2012). Center of excellence in research reporting in neurosurgery - diagnostic ontology. PLoS ONE 7 (5) : e36759. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0036759
Rights: Attribution 4.0 International
Abstract: Motivation: Evidence-based medicine (EBM), in the field of neurosurgery, relies on diagnostic studies since Randomized Controlled Trials (RCTs) are uncommon. However, diagnostic study reporting is less standardized which increases the difficulty in reliably aggregating results. Although there have been several initiatives to standardize reporting, they have shown to be sub-optimal. Additionally, there is no central repository for storing and retrieving related articles. Results: In our approach we formulate a computational diagnostic ontology containing 91 elements, including classes and sub-classes, which are required to conduct Systematic Reviews - Meta Analysis (SR-MA) for diagnostic studies, which will assist in standardized reporting of diagnostic articles. SR-MA are studies that aggregate several studies to come to one conclusion for a particular research question. We also report high percentage of agreement among five observers as a result of the interobserver agreement test that we conducted among them to annotate 13 articles using the diagnostic ontology. Moreover, we extend our existing repository CERR-N to include diagnostic studies. Availability: The ontology is available for download as an.owl file at: http://bioportal.bioontology.org/ontologies/3013. © 2012 Zaveri et al.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161982
ISSN: 19326203
DOI: 10.1371/journal.pone.0036759
Rights: Attribution 4.0 International
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