Knowledge Discovery From Sparse Pharmacokinetic Data

Ray R. Hashemi, Charles Epperson, Alexander A. Tyler, John F. Young

Research output: Contribution to book or proceedingConference articlepeer-review

4 Scopus citations

Abstract

In this research effort, we show that the following hypothesis is true: The independently verified sparse information secured from the scientific literature regarding the effects of methyl mercury on mice enables us to predict the effects of the methyl mercury on humans. The Rough Sets methodology is used in this endeavor.

Original languageAmerican English
Title of host publicationProceedings of the 2000 ACM Symposium on Applied Computing, SAC 2000
Pages75-79
Number of pages5
DOIs
StatePublished - Mar 19 2000

Publication series

NameProceedings of the 2000 ACM symposium on Applied computing - Volume 1

Scopus Subject Areas

  • Software

Keywords

  • Extrapolation
  • Methyl mercury effects on humans
  • Methyl mercury effects on mice
  • Rough sets
  • Sparse data

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