TY  - JOUR
AU  - Sajda Khan Gajdhar
AU  - Syed Mukith Ur Rahaman
AU  - Shaiq Gajdhar
TI  - Artificial intelligence in oral pathology: Current applications, challenges, and future prospects
JO  - Journal of Scientific Advances in Dentistry
PY  - 2026
VL  - 1
IS  - 2
SP  - 63
EP  - 67
DO  - 10.65929/JSAD.2026.1.2.006
SN  - 3139-4167
AB  - The field of Artificial Intelligence (AI) is revolutionizing the diagnostics industry and oral pathology is no exception. AI has been leveraged for disease diagnosis in the field of diagnostics and deep learning (DL) and machine learning (ML) algorithms have been employed for histopathological analysis, which has been automated. AI has also shown tremendous potential in diagnostics, with a particular emphasis on improving disease diagnosis, as well as in histopathology, where deep learning (DL) and machine learning (ML) algorithms have been utilized to automate the process. AI systems can classify oral lesions and grade dysplasia, analyze cytology slides, and correlate clinical and molecular data for individual patient treatment planning. Nevertheless, there are still hurdles, such as the lack of high-quality data, variability in staining and slide preparation procedures, a lack of interpretability and regulatory and ethics concerns. The aim of this review was to present the present situation of AI in oral pathology, its clinical applications, challenges and limitations, and future directions for research and clinical use.
UR  - https://dentistryjournal.org/volume/1/issue/2/article/artificial-intelligence-in-oral-pathology-current-applications-challenges-and-future-prospects
ER  -