2023 Volume 11 Issue 3
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Artificial Intelligence in Oral Pathology Practice– An Overview


Despite more recent medical achievements and a significant amount of information on various diseases, it is impossible to anticipate disease diagnosis and progress accurately. The advent of artificial intelligence (AI) has opened up many new possibilities for healthcare improvement and has ushered in a new era of increased exactitude in pathology. Artificial intelligence (AI) can be helpful in the diagnosis of diseases, in making prognostications, or in creating patient-specific treatment plans. AI can help pathologists in particular when they need to make important judgements quickly. It can eliminate human mistake from the judgement process, resulting in improved and standardised health care while diminishing the strain on the doctor. Pathologists are going to employ AI to find specific imaging indicators connected to disease processes in order to improve early diagnosis, ascertain prognosis, and select the treatments that are most likely to be successful. In the upcoming years, this trend is frequently anticipated to continue and change the pathology landscape.  Given the ageing population and rising patient volume, as well as the fact that there is a dearth of pathologists globally, this is especially crucial. Even though AI models have been effective, it has taken a while for them to be translated from research to clinical use. AI and pathologists working together can produce outcomes that are superior to what humans are capable of in terms of accuracy, consistency, timeliness, and utility. This review presents the components, emerging techniques and applications of AI in oral pathology.

How to cite this article
Kariamal N, Angadi PV. Artificial Intelligence in Oral Pathology Practice– An Overview. Ann Dent Spec. 2023;11(3):82-6. https://doi.org/10.51847/AQAJtO9N1U
Kariamal, N., & Angadi, P. V. (2023). Artificial Intelligence in Oral Pathology Practice– An Overview. Annals of Dental Specialty, 11(3), 82-86. https://doi.org/10.51847/AQAJtO9N1U
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