NCBI PubMed Central
open access
Accuracy of large language models in the Turkish dental specialization examination (DUS): a multidimensional evaluation across disciplines and question formats.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Performance of large language models on undergraduate endodontic multiple-choice questions.#1167241
- Large Language Model Responses to Common Otolaryngological Questions: Evaluating Accuracy, Appropriateness, Readability, and Hallucinations.#615753
- The role of large language models in dental diagnosis, decision-making, and communication: A systematic review.#9718
- The role of large language models in dental diagnosis, decision-making, and communication: A systematic review#4664
- Large language model prompt engineering for medical education: A practical guide for the Australian and New Zealand College of Anaesthetists Final Examination.#988756
Record · ID 1204650
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive