Assessment of ChatGPT-generated medical Arabic responses for patients with metabolic dysfunction–associated steatotic liver disease
MASLD experts found that ChatGPT responses were accurate, complete, and comprehensible. The results support the increasing trend of leveraging the power of AI chatbots to revolutionize the dissemination of information for patients with MASLD. However, many AI-powered chatbots require further enhancement of scientific content to avoid the risks of circulating medical misinformation.
Authors
- Saleh A. Alqahtani (ORCID: https://orcid.org/0000-0003-2017-3526)
- Cesare Hassan (ORCID: https://orcid.org/0000-0001-7167-1459)
- Waleed Alomaim
- Faisal Abaalkhail
- Khalid Bzeizi (ORCID: https://orcid.org/0000-0001-5346-6240)
- Waleed Al-hamoudi (ORCID: https://orcid.org/0000-0002-2759-0894)
- Ali Albenmousa (ORCID: https://orcid.org/0000-0003-0195-380X)
- Reem AlAhmed (ORCID: https://orcid.org/0000-0001-6302-5932)
- Alessio Aghemo (ORCID: https://orcid.org/0000-0003-0941-3226)
- Saad Alghamdi (ORCID: https://orcid.org/0000-0003-4532-9128)
- Nicola Riccardo Pugliese (ORCID: https://orcid.org/0000-0001-6466-1412)
Institutions
- Humanitas University (IT)
- Alfaisal University (SA)
- Cornell University (US)
- King Faisal Specialist Hospital & Research Centre (SA)
- IRCCS Humanitas Research Hospital (IT)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1371/journal.pone.0317929
- Citations
- 4
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 9.92