The early diagnosis of cancer can facilitate subsequent clinical patient management. Artificial intelligence (AI) has been found to be promising for improving the diagnostic process. The aim of the present study is to increase the evidence on the application of AI to the early diagnosis of oral cancer through a scoping review. A search was performed in the PubMed, Web of Science, Embase and Google Scholar databases during the period from January 2000 to December 2020, referring to the early non-invasive diagnosis of oral cancer based on AI applied to screening. Only accessible full-text articles were considered. Thirty-six studies were included on the early detection of oral cancer based on images (photographs (optical imaging and enhancement technology) and cytology) with the application of AI models. These studies were characterized by their heterogeneous nature. Each publication involved a different algorithm with potential training data bias and few comparative data for AI interpretation. Artificial intelligence may play an important role in precisely predicting the development of oral cancer, though several methodological issues need to be addressed in parallel to the advances in AI techniques, in order to allow large-scale transfer of the latter to population-based detection protocols.

Background: Stress and anxiety have frequently been mentioned as possible factors related to the development of oral lichen planus (OLP), although this association remains controversial. Objective: To determine whether anxiety and depression constitute risk factors in the development of OLP. Material and Methods: Eighty patients diagnosed as having OLP were studied: anxiety was evaluated by the Hamilton Anxiety Scale and depression with the Montgomery-Asberg Depression Rating Scale. The results were contrasted with those obtained in a control series of the same number of subjects (n = 80) matched for age and sex. Results: Significantly greater anxiety and depression were observed among patients with OLP than in the control group. Odds ratios of 2.8 and 4.4 were obtained for anxiety and depression, respectively. Conclusion: Our findings suggest that anxiety and depression constitute risk factors that could influence the development of OLP.

Background: Thyroid disease has been mentioned to have a possible relation to the development of oral lichen planus (OLP). Objective: Because goiter is considered endemic in many countries, we proposed to determine whether thyroid disease constitutes a comorbidity of OLP. Methods: Two hundred and fifteen patients diagnosed as having OLP were evaluated concerning their serum thyroid-stimulating hormone and thyroxine (T4) levels. The results were contrasted with those obtained in control series of the same number of subjects matched for age and sex. Results: Diagnosis of thyroid disease was present in 15.3% of OLP patients (33/215) and in 5.2% (12/215) of the control group. In relation to OLP patients, the odds ratio of presence of thyroid disorders was 3.06 and that of using levothyroxine medication 3.21. Conclusions: In the present study, OLP patients were associated with thyroid disease, specifically with hypothyroidism. Because most thyroid patients need T4 treatment, our findings confirmed that OLP and thyroid disease could be comorbidities.