AI-Powered Clinical Decision Support in Dentistry: Comparative Evaluation of Large Language Models for Oral Medicine and Periodontal Diagnosis

01 April 2026 : Database Analysis

Rayan Mohammedfarooq Meer^{ABCE 1}, Abdullah Alqarni^{CDE 2}, Basem Mohammed Akily^{BEF 3}, Hattan Zaki^{DEF 3}, Mostafa Ibrahim Fayad

^{CDEF 4}, Mohammed Hosny H. AbdElaziz

^{DEF 4}, Mohamed Omar Elboraey^{ABCEF 1,5*}

DOI: 10.12659/MSM.951721

Med Sci Monit 2026; 32:e951721

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Introduction Material and Methods Results Discussion Conclusions Data Availability References

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Table 3 Friedman test results for all evaluation criteria.

Evaluation criteria	Chi-square	P value	Sample size	Significance level
Accuracy	28.155	<0.001	102	^***
Time efficiency	43.670	<0.001	102	^***
Ease of use	35.858	<0.001	102	^***
Clarity of explanation	44.427	<0.001	102	^***
Comprehensiveness	56.933	<0.001	102	^***
Ability to answer questions	45.756	<0.001	102	^***
Reliability	20.582	<0.001	102	^***
Diagnostic range	33.092	<0.001	102	^***
Significance levels: ^* ^ ^* ns – not significant. All criteria show statistically significant differences between AI models (

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