How can machine learning enhance toxicological data analysis?
Machine learning (ML) is increasingly being integrated into toxicological studies to enhance data analysis:
Pattern Recognition: ML algorithms can uncover patterns and associations in large datasets that may not be apparent through traditional analysis methods. Predictive Analytics: Machine learning models can predict the toxicological effects of new compounds, aiding in risk assessment and regulatory submissions. Automation: Automating repetitive tasks allows toxicologists to focus on more complex analyses and interpretation efforts. Personalized Toxicology: ML can help tailor toxicological assessments to individual genetic and environmental factors, providing more precise evaluations.
