Artificial intelligence-based data extraction for next generation risk assessment: Is fine-tuning of a large language model worth the effort?

To underpin scientific evaluations of chemical risks, agencies such as the European Food Safety Authority (EFSA) heavily rely on the outcome of systematic reviews, which currently require extensive manual effort. One specific challenge constitutes the meaningful use of vast amounts of valuable data from new approach methodologies (NAMs) which are mostly reported in an unstructured way in the scientific literature. In the EFSA-initiated project 'AI4NAMS', the potential of large language models (LLMs) was explored.

Life without quality. Reflections of a female focus group on life, health and kidney disease.

Focus groups are increasingly employed in clinical practice as their flexible structure permits the range and depth of experiences of health service users and chronically ill individuals to be explored and recorded. A focus group workshop on quality of life was held in March 2007 involving a group of patients either awaiting transplantation, following transplantation, or with a family member who had already undergone renal replacement therapy (RRT). After intensive discussion the group produced the following consensus points.