A hybrid machine learning approach using LBP descriptor and PCA for age-related macular degeneration classification in OCTA images

We propose a novel hybrid machine learning approach for age-related macular degeneration (AMD) classification to support the automated analysis of images captured by optical coherence tomography angiography (OCTA). The algorithm uses a Rotation Invariant Uniform Local Binary Patterns (LBP) descriptor to capture local texture patterns associated with AMD and Principal Component Analysis (PCA) to decorrelate texture features. The analysis is performed on the entire image without targeting any particular area. The study focuses on four distinct groups, namely, healthy; neovascular AMD (an advanced stage of AMD associated with choroidal neovascularisation (CNV)); non-neovascular AMD (AMD without the presence of CNV) and secondary CNV (CNV due to retinal pathology other than AMD). Validation sets were created using a Stratified K-Folds Cross-Validation strategy for limiting the overfitting problem. The overall performance was estimated based on the area under the Receiver Operating Characteristic (ROC) curve (AUC). The classification was conducted as a binary classification problem. The best performance achieved with the SVM classifier based on the AUC score for: (i) healthy vs neovascular AMD was 100 % , (ii) neovascular AMD vs non-neovascular AMD was 85 % ; (iii) CNV (neovascular AMD plus secondary CNV) vs non-neovascular AMD was 83 %

Fluoride level in drinking water and prevalence of dental fluorosis and dental caries among the school children: A descriptive cross-sectional study

Background: Fluoride is very critical for the normal development and caries resistance of enamel. However, fluoride level above1 part per million (PPM) will result in enamel hypoplasia. Aim: The study aims to estimate the fluoride level in the drinkingwater and the prevalence of dental fluorosis and dental caries among the schoolchildren in Al-Zulfi and Majmaah areas in Riyadhprovince of Saudi Arabia. Materials and Methods: Drinking water samples were analyzed from the study area, and screeningcamps were conducted for schoolchildren between 7 and 15 years of age, and 157 children were included in the study using simplerandom sampling. Written consent from the parents was obtained. The collected data were subjected to statistical analysis usingSPSS version 21. Results: The drinking water sample showed a fluoride level between 0.56 PPM and 0.09 PPM and 39 children(24.8%) had fluorosis. 9 (23%) of them had fluorosis in primary dentition and 30 in permanent dentition (76.9%). A mean of totalnumber of caries in permanent teeth is 1.87 and 2.35 in primary teeth. Conclusion: The drinking water in the study area hadfluoride below the optimal level with an increased prevalence of dental caries. However, the presence of dental fluorosis could beattributed to other sources of dietary fluorides. This research highlights the necessity for maintaining optimum level of fluoridein drinking water and monitoring fluoride intake from other dietary sources