In toxicology, ML can be applied in various ways, including:
1. Predicting Toxicity: ML algorithms can predict the toxicity of new compounds by analyzing existing data on similar substances. 2. Risk Assessment: ML models can assess the risk associated with exposure to different chemicals, helping in regulatory decision-making. 3. Data Integration: ML can integrate data from various sources, such as chemical structures, biological assays, and epidemiological studies, to provide a comprehensive understanding of toxicological effects.
