Abstract
Oral cancer is a global issue that poses challenges in both diagnosis and treatment. About 50% of cases are detected at an advanced stage, leading to a low 5-year survival rate. Visual assessments are conventionally employed in dental clinics for the detection of oral cancer, but, their precision is greatly influenced by the proficiency and knowledge of the practitioner, which can significantly differ. Furthermore, the subjective character of these tests might lead to inconsistencies in the diagnosis, hence increasing the probability of either an under- or overdiagnosis. Moreover, the diagnosis of oral cancer entails a substantial emotional burden as a result of protracted and intricate medical interventions, which in turn induces considerable worry in patients. In recent times, artificial intelligence has begun to assist in the diagnosis of oral cancer through many methods. AI-based diagnostic systems have the capability to analyse large amounts of data, including intraoral camera pictures, radiographs, and advanced imaging like MRI or CT scans. This allows them to detect even small changes and enhance image analysis. Thus, the present paper discusses the ways AI powered oral cancer detection can reduce the risks and increase accuracy to give better quality of life to patients.
Published Version
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