Developmental Toxicity Risk Assessment: A Rough Sets Approach

Ray R. Hashemi, F. Jelovsek, M. Razzaghi

Research output: Contribution to journalArticlepeer-review

Abstract

A rough-sets approach was applied to a data set consisting of animal study results and other compound characteristics to generate local and global (certain/possible) sets of rules for prediction of developmental toxicity in human subjects. A modified version of the rough-sets approach is proposed to allow the construction of an approximate set of rules to use for prediction in a manner similar to that of discriminant analysis. The modified rough-sets approach is superior in predictability to the original form of rough-sets methodology. In comparison to discriminant analysis, modified rough sets (approximate rules) appear to be better in overall classification, sensitivity, positive and negative predictive values. The findings were supported by applying the modified rough sets and discriminant analysis on a test data set generated from the original data set by using a resampling plan.
Original languageAmerican English
JournalInternational Journal of Methods of Information in Medicine
Volume32
StatePublished - 1993

Keywords

  • Assessment
  • Developmental
  • Rough sets approach
  • Toxicity risk

DC Disciplines

  • Engineering
  • Computer Sciences

Fingerprint

Dive into the research topics of 'Developmental Toxicity Risk Assessment: A Rough Sets Approach'. Together they form a unique fingerprint.

Cite this