标题：PREDICTION OF ENDOCRINE SYSTEM AFFECTATION IN FISHER 344 RATS BY FOOD INTAKE EXPOSED WITH MALATHION, APPLYING NAIVE BAYES CLASSIFIER AND GENETIC ALGORITHMS
摘要：Background: Reported cases of uncontrolled use of pesticides and its produced effects by director indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shownthe results of the development and execution of an algorithm that predicts the possible effects inendocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. Methods: It was referred to ToxRefDB database in which different case studies in F344 ratsexposed to malathion were collected. The experimental data were processed using NaïveBayes (NB) machine learning classifier, which was subsequently optimized using geneticalgorithms (GAs). The model was executed in an application with a graphical user interfaceprogrammed in C#. Results: There was a tendency to suffer bigger alterations, increasing levels in the parathyroidgland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects onthe endocrine system by the ingestion of malathion. Females were more susceptible to sufferalterations in the pituitary gland with exposure times between 3 and 6 months. Conclusions: The prediction model based on NB classifiers allowed to analyze all the possiblecombinations of the studied variables and improving its accuracy using GAs. Excepting thepituitary gland, females demonstrated better resistance to contract effects by increasing levelson the rest of endocrine system glands.
关键词：ARTIFICIAL INTELLIGENCE; MACHINE LEARNING; ORGANOPHOSPHATE; RAT
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