EXPLAINABLE MACHINE LEARNING FOR PREDICTING MOLECULAR TOXICITY FROM PHYSICOCHEMICAL AND STRUCTURAL PROPERTIES
The prediction of molecular toxicity is becoming more and more critical for effective chemical safety assessment, drug development and environmental risk assessment. In this study, an explainable machine learning model for predicting molecular toxicity was developed using physicochemical descriptors and structural prop...