What Role Does Data Quality Play in Backpropagation for Toxicology?
Data quality is crucial for the success of backpropagation in toxicology. High-quality, well-annotated datasets ensure that the neural network can learn accurate patterns and relationships between chemical properties and their toxic effects. Poor-quality data can lead to incorrect predictions and unreliable models, which could have serious implications for public health and safety.
