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Improved Naïve Bayesian Modeling of Numerical Data for Absorption, Distribution, Metabolism and Excretion (ADME) Property Prediction
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (1995)
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inferred← citeshttps://doi.org/10.1002/0471266949.bmc122openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9780470567623.ch4openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9781119282594.ch1openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.drudis.2008.03.022openalex-snapshot
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