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- W4386150125 abstract "Blood centers are responsible for managing blood stocks so that they satisfy at a considerable level, in addition to guaranteeing a quality standard with the blood collected. Both factors are possible if there is a control of regular donors. Thus, this article proposes a computational model that predicts regular blood donors, whose methodology joins the results of association measures to determine the most likely characteristics of a donor, with the Naive Bayes algorithm. The proposed model presented results superior to 68% accuracy and 73% precision in predicting a regular blood donor." @default.
- W4386150125 created "2023-08-25" @default.
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- W4386150125 date "2023-06-27" @default.
- W4386150125 modified "2023-10-02" @default.
- W4386150125 title "Bayesian networks for blood donor prediction" @default.
- W4386150125 doi "https://doi.org/10.5753/sbcas.2023.230123" @default.
- W4386150125 hasPublicationYear "2023" @default.
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