“Improving Laboratory Animal Welfare with Advanced Data Science Methods“
In this presentation, Steven R. Talbot (Preclinical Data Science group at the Institute for Laboratory Animal Science at Hannover Medical School) will discuss key aspects of implementing data science methods in animal welfare assessment. This approach involves analyzing, estimating, and predicting humane endpoints, as well as utilizing a quantitative system for relative severity assessment using multidimensional input data. The webinar will focus on refining the decision-making process in welfare assessment within laboratory animal science, aiming to make it more evidence-based. The methods presented are highly beneficial for automated home cage monitoring and have significant translational value.