Oral mucosal lesions (OML) and oral potentially malignant disorders (OPMDs) have been identified as having the potential to transform into oral squamous cell carcinoma (OSCC). This research focuses on the human-in-the-loop-system named Healthcare Professionals in the Loop (HPIL) to support diagnosis through an advanced machine learning procedure. HPIL is a novel system approach based on the textural pattern of OML and OPMDs (anomalous regions) to differentiate them from standard regions of the oral cavity by using autofluorescence imaging. An innovative method based on pre-processing, e.g., the Deriche–Canny edge detector and circular Hough transform (CHT); a post-processing textural analysis approach using the gray-level co-occurrence matrix (GLCM); and a feature selection algorithm (linear discriminant analysis (LDA)), followed by k-nearest neighbor (KNN) to classify OPMDs and the standard region, is proposed in this paper. The accuracy, sensitivity, and specificity in differentiating between standard and anomalous regions of the oral cavity are 83%, 85%, and 84%, respectively. The performance evaluation was plotted through the receiver operating characteristics of periodontist diagnosis with the HPIL system and without the system. This method of classifying OML and OPMD areas may help the dental specialist to identify anomalous regions for performing their biopsies more efficiently to predict the histological diagnosis of epithelial dysplasia.

BackgroundHuman immunodeficiency virus (HIV) infection is a public health concern worldwide. The clinical manifestations include underweight and oral lesions. The objective of this study was to assess the relationship between oral pathologies and underweight among HIV-positive patients in Yaounde, Cameroon. MethodsWe conducted a cross-sectional study between February 1st and 30th June 2021 at Yaounde Central Hospital in Cameroon. A total of 205 HIV positive patients aged at least 18 years were recruited via consecutive sampling. The questionnaire consisted of sociodemographic information, anthropometric data, dietary habits, HIV history and treatment and oral examination data. The data were analysed with R software. Multivariate analysis was used to assess the risk of being underweight among HIV-positive patients with oral pathologies. A p value < 0.05 was considered to indicate statistical significance. ResultsThe prevalence of oral pathologies was 52.7% (95% CI: 45.6-59.6), and the main pathologies were candidiasis (40.5%, 95% CI: 33.7-47.5) and linear erythema (32.2%, 95% CI: 25.9-39.1). The prevalence of underweight was 20% (95% CI: 14.88-26.26). Binary logistic regression revealed that HIV-positive patients with oral pathologies were 10.89 (95% CI: 2.28-16.63) times more likely to be underweight than were HIV positive and AIDS patients without oral pathologies (p = 0.002). ConclusionOral candidiasis and linear erythema were common in HIV positive and AIDS patients. HIV-positive and AIDS patients with these oral pathologies were at higher risk of being underweight than were those without oral pathologies. The effective medical care of these patients must include oral and nutritional management.

BackgroundTooth decay and periodontal diseases are the main oral pathologies in the world. The prevalence of overweight in children has increased worldwide. Overweight children have alterations in the composition of saliva and excessive consumption of saturated fatty acids tend to slow the metabolism of carbohydrates in the oral cavity leading to tooth decay, periodontal disease and others oral disorders. The aim of this study was to assess the relationship between oral pathologies and overweight in pupils of primary schools of Cameroon.MethodsA cross-sectional study was carried out from June to August 2020 in four government primary schools selected through cluster sampling in Yaounde. 650 pupils aged between 6 and 11 years were enrolled. Data collected included anthropometric, oral pathologies, quality of oral hygiene and feeding habits. Data were analysed with the SPSS 26.0 statistical software and binary logistic regression was used to determine the risks of oral pathologies in overweight pupils. P-value of 0.05 was considered statistically significant.ResultsThe prevalence of overweight was 27% (95% CI: 23.5-30.5). The main oral pathologies was tooth decay (60.3%). Binary logistic regression revealed that overweight pupils were significantly 1.5 times more likely to develop tooth decay than non-overweight pupils (95% CI: 1.1-2.4).ConclusionOverweight, tooth decay are prevalent among pupils. Overweight pupils have a higher risk of developing tooth decay compared to non-obese pupils. An integrated package of oral and nutritional health promotion activities is necessary in primary schools in Cameroon.