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Artificial Intelligence chatbots in oral pathology: a scoping review of applications, accuracy, and limitations
Everton Freitas de Morais1, Maurília Raquel de Souto Medeiros2, Deborah Gondim Lambert Moreira2
1Graduate Program in Oral Biology and Department of Oral Diagnosis, School of Dentistry, University of Campinas, Piracicaba, SP, 13414-018, Brazil. evertonf@unicamp.br.
Purpose:
This scoping review aims to critically assess the applications, performance, and limitations of artificial intelligence (AI) chatbots in oral pathology.
Methods:
An electronic search was conducted in PubMed/MEDLINE, Embase, Scopus, and Science Direct from inception to March 2025. Studies were eligible if they evaluated chatbot use in oral pathology, including diagnostic support for oral lesions and cancers, patient education, and professional training.
Results:
From 761 records identified, 13 studies met the inclusion criteria. AI chatbots demonstrated potential to assist in diagnostics and patient education on oral diseases. Diagnostic accuracy was influenced by lesion type, patient characteristics, and whether multimodal inputs (e.g., images plus text) were provided, with higher accuracy observed when such data were included. Despite these strengths, chatbots frequently exhibited limitations such as inconsistent empathy, citation inaccuracies, and variable readability-issues that were recurrent across studies and highlight the need for professional oversight.
Conclusion:
AI chatbots show promise in supporting diagnostics and patient education in oral pathology. However, key limitations regarding accuracy, empathy, and information reliability necessitate robust validation and ethical safeguards before clinical adoption.
Prospero Registration:
CRD420251020464.
