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dc.contributor.authorYang, Yingjieen
dc.contributor.authorGuo, X.en
dc.contributor.authorLiu, Sifengen
dc.date.accessioned2019-01-15T09:48:12Z
dc.date.available2019-01-15T09:48:12Z
dc.date.issued2018-12-05
dc.identifier.citationGuo, X., Liu, S. and Yang, Y. (2019) A prediction method for plasma concentration by using a nonlinear grey Bernoulli combined model based on a self-memory algorithm. Computers in Biology and Medicine, 105, pp.81-91.en
dc.identifier.issn0010-4825
dc.identifier.urihttp://hdl.handle.net/2086/17430
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractThe goal of this work is to present and explore the application of a novel nonlinear grey Bernoulli combined model based on a self-memory algorithm, abbreviated as SA-NGBM, for modeling single-peaked sequences of time samples of acetylsalicylate plasma concentration following oral dosing. The self-memorization SA-NGBM routine reduces the dependence on a solitary initial value, as the initial state of the model utilizes multiple time samples. To test its forecasting performance, the SA-NGBM was used to extrapolate the plasma concentration predicted data, in comparison with the later time samples. The results were contrasted with those of the traditional optimized NGBM (ONGBM), exponential smoothing (ES) and simple moving average (SMA) using four popular accuracy and significance tests. That comparison showed that the SA-NGBM was much more accurate and efficient for matching the individual, nonlinear-system stochastic fluctuations than the existing ONGBM, ES and SMA models. The findings have potential applications for signal matching to similar small sample size, single-peaked, plasma concentration series.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectgrey prediction theoryen
dc.subjectnonlinear grey Bernoulli modelen
dc.subjectself-memory algorithmen
dc.subjectplasma concentrationen
dc.titleA prediction method for plasma concentration by using a nonlinear grey Bernoulli combined model based on a self-memory algorithmen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1016/j.compbiomed.2018.12.004
dc.researchgroupInstitute of Artificial Intelligence (IAI)en
dc.peerreviewedYesen
dc.funderFP7 MSCAen
dc.projectidFP7-PIIF-GA-2013-629051en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2018-12-04en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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