Researchers have developed a large language model-based tool to identify HIV-related stigma in clinical narratives, addressing a critical gap in health care tools for people living with HIV. The study demonstrates that fine-tuning models like GatorTron-large and using few-shot prompting with generative LLMs significantly improves the accuracy of detecting stigma, which can help improve mental health outcomes and engagement in care for PLWH.
Read the full article at arXiv cs.CL (NLP)
Want to create content about this topic? Use Nemati AI tools to generate articles, social posts, and more.





