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Methods Inf Med 1993; 32(01): 47-54
DOI: 10.1055/s-0038-1634890
Original Article
Schattauer GmbH

Developmental Toxicity Risk Assessment: A Rough Sets Approach

R. R. Hashemi
1   Department of Computer and Information Science, University of Arkansas at Little Rock, Little Rock, AR
,
F. R. Jelovsek
2   Department of Obstetrics and Gynecology, East Tennessee State University College of Medicine, Johnson City, TN
,
M. Razzaghi
3   Department of Mathematics and Computer Science, Bloomsburg University, Bloomsburg, PA, USA
› Author Affiliations
Further Information

Publication History

Publication Date:
06 February 2018 (online)

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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.

Key-Words

Risk Assessment - Rough Sets - Rule Learning - Information Systems
 

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