Machine Learning Approaches for Toxicological Risk Assessment in Food Systems
This publication explores the use of machine learning techniques in evaluating toxicological risks associated with chemical compounds present in food systems. The study applies predictive modeling to assess exposure levels and potential health risks, utilizing data from laboratory experiments and environmental monitoring sources. Various algorithms were tested to improve the accuracy of toxicity predictions and […]