How Do Machine Learning Algorithms Contribute to Toxicology?
Machine learning algorithms contribute to toxicology by enabling the analysis of complex datasets and the identification of patterns that may not be evident through traditional methods. These algorithms can be used to develop predictive models, identify biomarkers of toxicity, and improve the accuracy of risk assessments. The ability to learn from data and improve over time makes machine learning a powerful tool in toxicological research.
