Probabilistic mathematical modelling to predict the red cell phenotyped donor panel size.
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| Title: | Probabilistic mathematical modelling to predict the red cell phenotyped donor panel size. |
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| Authors: | Best D; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia., Burrage K; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia., Burrage P; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia., Donovan D; School of Mathematics and Physics, University of Queensland, Brisbane, Queensland, Australia., Ginige S; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia., Powley T; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia., Thompson B; School of Mathematics and Physics, University of Queensland, Brisbane, Queensland, Australia., Daly J; Australian Red Cross Lifeblood, Brisbane, Queensland, Australia. |
| Source: | PloS one [PLoS One] 2022 Nov 11; Vol. 17 (11), pp. e0276780. Date of Electronic Publication: 2022 Nov 11 (Print Publication: 2022). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0276780 |
