What question did this study set out to answer?

The research aims to assess how well large language models respond to common patient questions in restorative dentistry regarding accuracy, empathy, and readability.

April 12, 2026BMC Oral HealthOpen Access

From algorithms to empathy: can large language models effectively answer patients’ questions in restorative dentistry?

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Authors

SCSuzan CangülDicle University MTMakbule TaşyürekDicle University TTTuba TunçDicle University

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Implication

Compares large language models’ accuracy, empathy, and readability in answering dental patient queries, indicating performance variation.

Key Points

The research aims to assess how well large language models respond to common patient questions in restorative dentistry regarding accuracy, empathy, and readability.
Compared responses from four large language models: ChatGPT-5, Gemini 2.5 Pro, DeepSeek-V3.2, and Claude Sonnet-4.5.
Evaluated accuracy and empathy using Likert-type scales by experienced evaluators.
Assessed readability with various online indexes such as FRES and FKGL.
Utilized ANOVA/Kruskall-Wallis for group comparisons based on data distribution.
DeepSeek-V3.2 achieved the highest accuracy (4.8 ± 0.5) and empathy scores (1.96 ± 0.2).
Statistically significant differences in accuracy and empathy were found among models (p < 0.001).
DeepSeek-V3.2 demonstrated superior readability with mean FRES values of 60.85 ± 8.2.

Cite This Study

Cangül et al. (2026) studied this question.

synapsesocial.com/papers/69db36a04fe01fead37c4ac3 https://doi.org/10.1186/s12903-026-08255-0

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Implication

Compares large language models’ accuracy, empathy, and readability in answering dental patient queries, indicating performance variation.

From algorithms to empathy: can large language models effectively answer patients’ questions in restorative dentistry?

Discussion

Member takes

Implication

Key Points

Cite This Study

From algorithms to empathy: can large language models effectively answer patients’ questions in restorative dentistry?

Discussion

Member takes

Implication

Key Points

Cite This Study

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