How Do Machine Learning Algorithms Work in Toxicology?
ML algorithms in toxicology typically involve training a model on a dataset that includes various chemical properties and associated toxicological outcomes. Once trained, the model can predict the toxicity of new, untested compounds. Common algorithms used include decision trees, random forests, support vector machines (SVM), and neural networks.
