How does machine learning enhance risk assessment?
Risk assessment is a critical component of toxicological evaluation, determining the likelihood of adverse effects occurring in exposed populations. ML algorithms improve risk assessment by analyzing complex datasets to identify potential risk factors and their interactions. For example, ML can integrate data from various sources like epidemiological studies, exposure data, and chemical properties to provide a comprehensive risk profile, facilitating more informed decision-making.
