Interpretability in toxicology models is important for several reasons:
Regulatory Compliance: Regulatory agencies, such as the FDA and EPA, require transparent models to understand how predictions are made. Risk Assessment: Understanding the factors driving a model's predictions helps toxicologists in conducting thorough risk assessments. Model Validation: Interpretable models are easier to validate and verify, ensuring that they are based on sound biological principles. Trust: Interpretability fosters trust among stakeholders, including scientists, regulators, and the public.
