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Autoregressive modelling of chromatographic signals from urine samples for prostate cancer diagnosis

dc.contributor.authorMedina Delgado, Byron
dc.contributor.authorSoto Vergel, Angelo Joseph
dc.contributor.authorPALACIOS ALVARADO, WLAMYR
dc.date.accessioned2021-11-08T21:59:47Z
dc.date.available2021-11-08T21:59:47Z
dc.date.issued2021-06-09
dc.identifier.urihttp://repositorio.ufps.edu.co/handle/ufps/781
dc.description.abstractThis article evaluates autoregressive modeling as a feature extraction method in a database of chromatographic signals from urine samples for non-invasive diagnostic support of prostate cancer in response to the research question: Can chromatographic signals from urine be characterized and used as a non-invasive method for cancer diagnosis? For this purpose, a database of 18 patients, 9 diagnosed with prostate cancer and 9 control patients, is consolidated, statistical methods are implemented to generate autoregressive coefficients from the data signals, and finally, the principal component analysis technique is applied for cross-class classification. As a result, a correct classification was obtained in the total number of samples validating the autoregressive modelling as a feature extraction method in contrast to the conventional methodology usually followed in chromatographic signal processing.eng
dc.format.extent06 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherJournal of Physics: Conference Seriesspa
dc.relation.ispartofJournal of Physics: Conference Series
dc.rightsContent from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.eng
dc.sourcehttps://iopscience.iop.org/article/10.1088/1742-6596/1938/1/012011/metaspa
dc.titleAutoregressive modelling of chromatographic signals from urine samples for prostate cancer diagnosiseng
dc.typeArtículo de revistaspa
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dc.identifier.doihttps://doi.org/10.1088/1742-6596/1938/1/012011
dc.publisher.placeReino Unidospa
dc.relation.citationeditionVol.1938 No.1.(2021)spa
dc.relation.citationendpage6spa
dc.relation.citationissue1(2021)spa
dc.relation.citationstartpage1spa
dc.relation.citationvolume1938spa
dc.relation.citesSoto-Vergel, A. J., Medina-Delgado, B., & Palacios-Alvarado, W. (2021, May). Autoregressive modelling of chromatographic signals from urine samples for prostate cancer diagnosis. In Journal of Physics: Conference Series (Vol. 1938, No. 1, p. 012011). IOP Publishing.
dc.relation.ispartofjournalJournal of Physics: Conference Seriesspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAtribución 4.0 Internacional (CC BY 4.0)spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
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oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa


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