Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology · 2025
Exploring the Role of Artificial Intelligence in Oral Pathology: Diagnostic and Prognostic Implications.
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Alsanie Ibrahim S, Qannam Ahmed, Bello Ibrahim O, Khurram Syed Ali
Аннотация
OBJECTIVES: This narrative review aims to briefly discuss the concepts of artificial intelligence (AI), explore its role in oral pathology and oncology, and shed light on AI's potential in addressing diagnostic and prognostic challenges in the field. Additionally, future perspectives of AI are postulated.
METHODS: A literature search using PubMed, EMBASE, Web of Science, and Scopus for studies published before February 2025 related to AI usage in the assessment of oral diseases such as oral potentially malignant disorders and transformation to oral cancer, oral squamous cell carcinoma, salivary gland tumors, and odontogenic tumors.
RESULTS: Numerous investigative efforts have been directed at AI applications for diagnostic, risk assessment, and prognostication of oral diseases, although these are still relatively in their infancy, and more still needs to be done to refine these tools to make them overcome all the challenges that are being encountered.
CONCLUSIONS: While AI does not seek to replace oral pathologists but supplement their efforts, it has an immense potential to revolutionize oral pathology practice in the years to come. AI applications would greatly improve diagnostic accuracy, enhance epidemiological surveillance of diseases, drive the profession toward more personalized patient care and ultimately improve patient outcomes beyond the current level.
METHODS: A literature search using PubMed, EMBASE, Web of Science, and Scopus for studies published before February 2025 related to AI usage in the assessment of oral diseases such as oral potentially malignant disorders and transformation to oral cancer, oral squamous cell carcinoma, salivary gland tumors, and odontogenic tumors.
RESULTS: Numerous investigative efforts have been directed at AI applications for diagnostic, risk assessment, and prognostication of oral diseases, although these are still relatively in their infancy, and more still needs to be done to refine these tools to make them overcome all the challenges that are being encountered.
CONCLUSIONS: While AI does not seek to replace oral pathologists but supplement their efforts, it has an immense potential to revolutionize oral pathology practice in the years to come. AI applications would greatly improve diagnostic accuracy, enhance epidemiological surveillance of diseases, drive the profession toward more personalized patient care and ultimately improve patient outcomes beyond the current level.