Large language models and the future of rheumatology: assessing impact and emerging opportunities

Abstract

Purpose of review Large language models (LLMs) have grown rapidly in size and capabilities as more training data and compute power has become available. Since the release of ChatGPT in late 2022, there has been growing interest and exploration around potential applications of LLM technology. Numerous examples and pilot studies demonstrating the capabilities of these tools have emerged across several domains. For rheumatology professionals and patients, LLMs have the potential to transform current practices in medicine. Recent findings Recent studies have begun exploring capabilities of LLMs that can assist rheumatologists in clinical practice, research, and medical education, though applications are still emerging. In clinical settings, LLMs have shown promise in assist healthcare professionals enabling more personalized medicine or generating routine documentation like notes and letters. Challenges remain around integrating LLMs into clinical workflows, accuracy of the LLMs and ensuring patient data confidentiality. In research, early experiments demonstrate LLMs can offer analysis of datasets, with quality control as a critical piece. Lastly, LLMs could supplement medical education by providing personalized learning experiences and integration into established curriculums. Summary As these powerful tools continue evolving at a rapid pace, rheumatology professionals should stay informed on how they may impact the field.