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Optimal selection of a battery of tests: a multiobjective optimization methodology
S L Hu1, Y Y Haimes, R S Galen
1Systems Engineering Department, Case Western Reserve University, Cleveland, Ohio 44106.
Abstract:
The general problem of selecting a battery of tests for diagnostic purposes is discussed and multiobjective optimization methodology is applied to solve it, with battery selection being based on performance indices such as sensitivity, specificity, and the cost of testing. For a battery of tests, the extended majority rule is developed and used to interpret the compound test results. The major advantage of the model developed in this paper is that it can generate a set of noninferior batteries without requiring the calculation of all possible combinations of tests. An example in which the method is applied to a real problem--the selection of short-term tests to detect the carcinogenicity of chemicals--is discussed.
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