International Journal of Preventive Medicine (Int J Prev Med)2008-7802112016092717361736ENDepartment of Mechatronics Engineering, Faculty of Engineering, Nueva Granada Military University, BogotáDepartment of Mechatronics Engineering, Faculty of Engineering, Nueva Granada Military University, BogotáDepartment of Mechatronics Engineering, Faculty of Engineering, Nueva Granada Military University, Bogotá20160927<p><strong>Background: </strong>Reported cases of uncontrolled use of pesticides and its produced effects by direct<br />or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown<br />the results of the development and execution of an algorithm that predicts the possible effects in<br />endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion.</p><p><strong>Methods:</strong> It was referred to ToxRefDB database in which different case studies in F344 rats<br />exposed to malathion were collected. The experimental data were processed using Na&iuml;ve<br />Bayes (NB) machine learning classifier, which was subsequently optimized using genetic<br />algorithms (GAs). The model was executed in an application with a graphical user interface<br />programmed in C#.</p><p><strong>Results:</strong> There was a tendency to suffer bigger alterations, increasing levels in the parathyroid<br />gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between<br />739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on<br />the endocrine system by the ingestion of malathion. Females were more susceptible to suffer<br />alterations in the pituitary gland with exposure times between 3 and 6 months.</p><p><strong>Conclusions:</strong> The prediction model based on NB classifiers allowed to analyze all the possible<br />combinations of the studied variables and improving its accuracy using GAs. Excepting the<br />pituitary gland, females demonstrated better resistance to contract effects by increasing levels<br />on the rest of endocrine system glands.</p><p><strong>Keywords:</strong> Artificial intelligence, machine learning, organophosphate, rat</p>http://ijpm.mui.ac.ir/index.php/ijpm/article/view/1736http://ijpm.mui.ac.ir/index.php/ijpm/article/download/1736/2025