Evaluation of large language models in pediatric dentistry: a Bloom’s taxonomy-based analysis
This study aimed to evaluate the performance of three large language models (LLMs)-ChatGPT-4.0, Claude 3.5 Sonnet, and DeepSeek R1-in answering multiple-choice questions (MCQs) related to pediatric dentistry. Accuracy and justification quality were analyzed using Bloom's taxonomy.
Authors
- Raju Biswas (ORCID: https://orcid.org/0000-0002-6467-1511)
- Alka Mukhopadhyay (ORCID: https://orcid.org/0000-0002-2989-7507)
- Santanu Mukhopadhyay (ORCID: https://orcid.org/0000-0002-7810-987X)
Institutions
- Amazon (United States) (US)
- Malda Medical College and Hospital (IN)
- North Bengal University (IN)
Publication Details
- Journal
- Folia Medica
- Published
- 2025-08-14
- DOI
- https://doi.org/10.3897/folmed.67.e154338
- Citations
- 2
- Primary Topic
- Interpreting and Communication in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 5.63