Poster: Classifying primary outcomes in rheumatoid arthritis: Knowledge discovery from clinical trial metadata

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dc.contributor.authorFeng, Yuanyuan
dc.contributor.authorJaneja, Vandana P.
dc.contributor.authorYesha, Yelena
dc.contributor.authorRishe, Naphtali
dc.contributor.authorGrasso, Michael A.
dc.contributor.authorNiskar, Amanda
dc.date.accessioned2018-10-31T18:35:31Z
dc.date.available2018-10-31T18:35:31Z
dc.date.issued2015-12-03
dc.description2015 IEEE 5th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)en_US
dc.description.abstractEarly prediction of treatment outcomes in RA clinical trials is critical for both patient safety and trial success. We hypothesize that an approach employing metadata of clinical trials could provide accurate classification of primary outcomes before trial implementation. We retrieved RA clinical trials metadata from ClinicalTrials.gov. Four quantitative outcome measures that are frequently used in RA trials, i.e., ACR20, DAS28, and AE/SAE, were the classification targets in the model. Classification rules were applied to make the prediction and were evaluated. The results confirmed our hypothesis. We concluded that the metadata in clinical trials could be used to make early prediction of the study outcomes with acceptable accuracy.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/7344722en_US
dc.format.extent2 pagesen_US
dc.genreconference papers and proceedings pre-printen_US
dc.identifierdoi:10.13016/M2GQ6R609
dc.identifier.citationYuanyuan Feng, Vandana P Janeja, Yelena Yesha, Naphtali Rishe, Michael A. Grasso, and Amanda Niskar, Poster: Classifying primary outcomes in rheumatoid arthritis: Knowledge discovery from clinical trial metadata, 2015 IEEE 5th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS) , DOI: 10.1109/ICCABS.2015.7344722en_US
dc.identifier.uri10.1109/ICCABS.2015.7344722
dc.identifier.urihttp://hdl.handle.net/11603/11810
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 2015 IEEE
dc.subjectdata miningen_US
dc.subjectclinical trials metadataen_US
dc.subjectrheumatoid arthritisen_US
dc.subjectoutcome predictionen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.subjectpattern classificationen_US
dc.subjectmeta dataen_US
dc.subjectmedical computingen_US
dc.titlePoster: Classifying primary outcomes in rheumatoid arthritis: Knowledge discovery from clinical trial metadataen_US
dc.title.alternativeClassifying primary outcomes in rheumatoid arthritis: Knowledge discovery from clinical trial metadata
dc.typeTexten_US

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