Exploring the potential of large language models in identifying metabolic dysfunction‐associated steatotic liver disease: A comparative study of non‐invasive tests and artificial intelligence‐generated responses
GPT-4 achieved performance comparable to traditional risk scores in diagnosing MASLD and exhibited improved convenience, versatility and the capacity to offer user-friendly outputs. The integration of GPT-4V highlights the capacities of LLMs in handling both textual and visual medical data, reinforcing their expansive utility in healthcare practice.
Authors
- Qi Li (ORCID: https://orcid.org/0000-0001-6974-0347)
- Congzhuo Jia (ORCID: https://orcid.org/0000-0001-6143-7044)
- Yuhu Guo (ORCID: https://orcid.org/0009-0007-5398-6845)
- Wanying Wu
Institutions
- Hebei North University (CN)
- University of Manchester (GB)
- Guangdong Academy of Medical Sciences (CN)
- Guangdong Provincial People's Hospital (CN)
Publication Details
- Journal
- Liver International
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1111/liv.16112
- Citations
- 5
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.93
Funders
- Guangdong Provincial People's Hospital