What Role does Machine Learning Play in Toxicity Prediction?
Machine learning is transforming toxicity prediction by offering advanced analytical tools to process vast amounts of data. Algorithms can identify patterns and relationships within chemical databases that might be missed by traditional methods. Machine learning models, such as deep learning and neural networks, can improve the accuracy of predictions by continuously learning from new data. These models are particularly useful for analyzing complex datasets and can significantly reduce the need for animal testing.
