Dental Students' Knowledge, Attitudes and Perceptions of Artificial Intelligence Tools to Aid in the Diagnosis of Oral Cancer and Oral Potentially Malignant Disorders
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool in dentistry, particularly in the early detection of oral cancer (OC) and oral potentially malignant disorders (OPMDs). Data focused on European dental students and their knowledge/attitudes towards the use of AI for diagnosing OC/OPMDs are limited. METHODS: A cross-sectional online survey was conducted among final-year dental students from six European countries. The questionnaire assessed knowledge, attitudes, and perceived barriers regarding AI in the diagnosis of OC and OPMDs. Data were analysed using descriptive and comparative statistics to evaluate differences between countries. RESULTS: A total of 328 students participated (75% female, 25% male). Most students stated that they had not received formal training in AI (61%) and emphasised the need to incorporate such training into the dental curriculum (47%). Students from Portugal had highest overall knowledge scores, but at the same time, lowest overall attitude scores. The most commonly perceived barrier was insufficient training (87.8%). CONCLUSION: Final-year dental students demonstrate positive attitudes towards AI aiding in diagnosis of OC and OPMDs, although significant knowledge and skill gaps remain. Integrating structured AI education into dental curricula is essential to prepare future academics and clinicians for responsible and effective AI use.
Source: Oral Diseases
DOI: 10.1111/odi.70225
Authors: Vlaho Brailo, Rosa María Lopez‐Pintor, Molly Harte, Ana Andabak Rogulj, Danica Vidović Juras, Ivana Škrinjar, Marcio Diniz Freitas, Jacobo Limeres Posse, Luis Monteiro, Luis M. Silva, Jean‐Cristophe Fricain, Adrien Naveau, Giovanni Lodi, Niccolò Lombardi, Elena Varoni, José López López, Sonia Egido Moreno, Raj Ariyaratnam, Ali Abdullah Alqarni, Richeal Ní Ríordáin, Owen Addison, Yunpeng Li, Faleh Tamimi, Rui Albuquerque
Institutions: University Hospital Centre Zagreb, University of Zagreb, Universidad Complutense de Madrid, Guy's Hospital, Guy's and St Thomas' NHS Foundation Trust, Universidade de Santiago de Compostela, Cooperativa de Ensino Superior Politécnico e Universitário, Instituto de Investigação e Formação Avançada em Ciências e Tecnologias da Saúde, Université de Bordeaux, Inserm, Centre Hospitalier Universitaire de Bordeaux, Laboratory for the Bioengineering of Tissues, University of Milan, Institut d'Investigació Biomédica de Bellvitge, Universitat de Barcelona, University of Manchester, Taif University, University College Cork, King's College London, McGill University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,990
OpenAlex ID: W7128957323