Accuracy and Reproducibility of Different Artificial Intelligence Chatbots’ Responses to Patient-Based Vitreoretinal Questions: A Comparative Study
ChatGPT-5.o and DeepSeek R1 approached high accuracy and reproducibility comparable to clinical standards, indicating potential as patient-education tools in vitreoretinal care. However, variability across models and disease categories highlights the need for cautious clinical adoption and continued optimization to ensure safe, reliable information delivery.
Authors
- Mohammed Rashad Baker (ORCID: https://orcid.org/0000-0001-6986-4921)
- Motasem Al-Latayfeh (ORCID: https://orcid.org/0000-0003-2107-8213)
- Dalia Attar
- Seren Al Beiruti
- Rami Al-Dwairi (ORCID: https://orcid.org/0000-0002-4187-4527)
- Abdelwahab Aleshawi
- Mo'men Dayeh
- Walaa Awad
- Zainah Abu Khalil
- Elaf Jarrah
- Omar El-Mulki
- Lina Alma’aitah
- Zaina Qaddoumi
Institutions
- University of Jordan (JO)
- University of Miami (US)
- Jordan University of Science and Technology (JO)
- Hashemite University (JO)
- The Farah Hospital (JO)
Publication Details
- Journal
- Clinical ophthalmology
- Published
- 2026-02-01
- DOI
- https://doi.org/10.2147/opth.s580133
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00