EXPLAINING DEVELOPMENTAL NEUROTOXICITY BY XAI

Abstract

Chemical exposure can cause formative neurotoxicity, which requires fast and exact testing techniques. Human physiology presents various challenges for current techniques such as human essential cell culture examines, in vivo animal examinations, and tests of animal essential cell cultures. Research in this study used joining explainable artificial intelligence (XAI) with XGBoost AI (ML) models that were prepared to utilize binary classification as a strong mix of datasets to identify genes that may be associated with neurotoxicity. Significant genes were found and connected to the progression of neurotoxicity after SHAP values were effectively integrated into the ML models.