Large language model triaging of simulated nephrology patient inbox messages
ChatGPT-4 demonstrated high accuracy in triaging nephrology patient messages, highlighting the potential for AI-driven triage systems to enhance operational efficiency and improve patient care in outpatient clinics.
Authors
- Wisit Cheungpasitporn (ORCID: https://orcid.org/0000-0001-9954-9711)
- Iasmina Craici
- Jing Miao (ORCID: https://orcid.org/0000-0003-0642-9740)
- Justin H. Pham (ORCID: https://orcid.org/0009-0009-5913-7363)
- Supawadee Suppadungsuk (ORCID: https://orcid.org/0000-0003-1597-2411)
- Charat Thongprayoon (ORCID: https://orcid.org/0000-0002-8313-3604)
- Priscilla Koirala (ORCID: https://orcid.org/0000-0002-1027-8597)
Institutions
- Mayo Clinic (US)
- Mahidol University (TH)
- Mayo Clinic in Arizona (US)
- Ramathibodi Hospital (TH)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2024-09-09
- DOI
- https://doi.org/10.3389/frai.2024.1452469
- Citations
- 8
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.96