RESUMEN
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. Models from the GPT family, where GPT refers to Generative Pre-trained Transformer, were used for searching, extracting, and integrating data from scientific publications for NAM-based risk assessment. A case study on bisphenol A (BPA), a substance of very high concern due to its adverse effects on human health, focused on the structured extraction of information on test systems measuring biologic activities of BPA. Fine-tuning of a GPT-3 model (Curie base model) for extraction tasks was tested and the performance of the fine-tuned model was compared to the performance of a ready-to-use model (text-davinci-002). To update findings from the AI4NAMS project and to check for technical progress, the fine-tuning exercise was repeated and a newer ready-to-use model (text-davinci-003) served as comparison. In both cases, the fine-tuned Curie model was found to be superior to the ready-to-use model. Performance improvement was also obvious between text-davinci-002 and the newer text-davinci-003. Our findings demonstrate how fine-tuning and the swift general technical development improve model performance and contribute to the growing number of investigations on the use of AI in scientific and regulatory tasks.
RESUMEN
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. Before talking about quality of life, physicians should call us by our names, instead of by the names of our diseases. The true disease is the ignorance of diversity. The life of a person with a chronic disease is entangled with the disease and with the fear of the disease. It is impossible to consider one's disease separately from one's life, loves, failures, families, and dreams. To evaluate the quality of our life means knowing us, as people. We do not need other numbers. Physicians often see us as boxes, with a disease inside. That's not what we are. We need time. Discussions about the quality of life should include the people around us. The disease steals a lot from you, but it also gives you something in return. We do not feel sick. The main result was to highlight the close relationship between quality of life and quality of care. Underlining the importance of a global approach to health, and the role of the physician as a leader in all aspects of care.
