Utility of Large Language Models for Health Care Professionals and Patients in Navigating Hematopoietic Stem Cell Transplantation: Comparison of the Performance of ChatGPT-3.5, ChatGPT-4, and Bard.
Elisabetta XueDara Bracken-ClarkeGiovanni Maria IannantuonoHyoyoung Choo-WosobaJames L GulleyCharalampos S FloudasPublished in: Journal of medical Internet research (2024)
In conclusion, despite LLMs' potential capability in confronting challenging medical topics such as HSCT, the presence of mistakes and lack of clear references make them not yet appropriate for routine, unsupervised clinical use, or patient counseling. Implementation of LLMs' ability to access and to reference current and updated websites and research papers, as well as development of LLMs trained in specialized domain knowledge data sets, may offer potential solutions for their future clinical application.
Keyphrases
- healthcare
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- machine learning
- palliative care
- peritoneal dialysis
- prognostic factors
- autism spectrum disorder
- acute myeloid leukemia
- human health
- risk assessment
- smoking cessation
- quality improvement
- big data
- climate change
- body composition
- deep learning
- high intensity
- patient reported