Center of excellence in research reporting in neurosurgery--diagnostic ontology.
BACKGROUND
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.


BACKGROUND
The ontology is available for download as an.owl file at: http://bioportal.bioontology.org/ontologies/3013.
Universität Leipzig, Institut für Informatik, Leipzig, Saxony, Germany.
Amrapali
A
Zaveri
Jatin
J
Shah
Shreyasee
S
Pradhan
Clarissa
C
Rodrigues
Jacson
J
Barros
Beng Ti
BT
Ang
Ricardo
R
Pietrobon
D035843:Biomedical Research / Q000592:standards*; D019317:Evidence-Based Medicine / Q000592:standards*; D006801:Humans; D009493:Neurosurgery / Q000592:standards*