Harnessing AI Dentistry for Oral Ulcer Diagnosis

The fusion of artificial intelligence (AI) and healthcare has been a game-changer in medical diagnosis, prognosis prediction, and the formulation of patient-specific treatment strategies. 

Within the dental field, AI is proving to be a valuable ally, aiding dentists in swift decision-making, reducing errors, and ultimately enhancing the quality of medical care. The focus of this study is the integration of AI in the diagnosis of various types of mouth ulcers, which is a critical aspect of oral healthcare.

Methodology: A Comprehensive Review

To conduct this study, the researchers followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. These standards ensure a methodical and well-structured approach to the review process. The review encompassed an extensive search of reliable literature sources, including PubMed, Scopus, Embase, Web of Science, Ovid, Global Health, and PsycINFO. 

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The research covered the period from June 28, 2018, to June 28, 2023. The search was meticulously designed, utilising key terms such as AI, oral health, oral ulcers, oral herpes simplex, oral lichen planus, pemphigus vulgaris, recurrent aphthous ulcer (RAU), oral cancer, premalignant and malignant disorders, among others.

AI’s Role in Oral Ulcer Classification

The study not only surveyed existing literature but also ventured into the creation of an AI framework aimed at automating the categorisation of oral ulcers using clinical photographs. This AI model outperformed current convolutional neural network image categorisation techniques and exhibited commendable precision in oral ulcer classification. 

While the results showcase the potential of AI in identifying oral ulcers accurately, it’s imperative to note that the technique’s practical application necessitates further validation and training with a more extensive dataset before it can be employed in clinical settings.

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Shaping the Future of Oral Healthcare

The adoption of deep learning and deep neural networks, along with improved algorithms, has opened the door to innovative approaches to diagnosing oral ulcers. This technology has the potential to facilitate the quick, non-invasive, cost-effective, and practical assessment of the effectiveness of cancer treatment. 

Moreover, the categorisation and identification of RAU lesions using non-intrusive oral images revealed promising accuracy and potential for future clinical application. Researchers also identified relevant variables associated with RAU that could serve as input data for building artificial neural networks capable of predicting RAU.

The Road Ahead

As the study highlights the promising impact of AI in dentistry, particularly in diagnosing oral ulcers, it sets the stage for future advancements. AI’s integration into oral healthcare, backed by comprehensive data and improved AI models, could significantly enhance diagnostic accuracy and patient outcomes. The journey towards leveraging AI in the dental field is still in its early stages, but the potential is immense.