Performance of large language models in providing patient- oriented information on gingival recession: a comparative study
Sultan Albeshri · 2026
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Description
Sultan Albeshri compares three large language models in a 2026 study on patient answers about gum recession. Patients now ask chatbots health questions first, and dental topics are no exception. Twenty standard patient questions on receding gums went to each of three leading models.
Five gum specialists graded the sixty answers for accuracy, completeness, and personal preference. Accuracy and completeness came out equal across the models. One model answered fastest and with the fewest words, while the other two split the top preference spots. Post treatment care earned the highest accuracy marks for all three. The author backs the tools as teaching aids beside, not instead of, a dentist's advice.
Catalog record
| CREATOR | Sultan Albeshri |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 29 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |