Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Background: Congenital heart disease is one of the most common developmental anomalies in children. These patients commonly have poor oral health that increase caries risk. Dental management of children with congenital heart disease requires special attention, because of their heightened susceptibility to infectious endocarditis. The aims of this study were to assess the severity of dental caries of primary and permanent teeth and treatment needs in relation to nutritional indicator (Body Mass Index) among children with congenital heart disease. Materials and Methods: In this case-control study, case group consisted of 399 patients aged between 6-12 years old with congenital heart disease were examined for dental status in Ibn Al-Bitar spec

In order to investigate the presence of methicillin or multidrug resistant Staphylococcus aureus in food-chain especially Cows raw milk and white raw soft cheese and its whey, a total of 30 samples were collected randomly from different markets in Baghdad Province during December 2012 till February 2013, in which samples were analyzed by a standard isolation protocols of food microbiology with some modification processing by new, modern and rapid technology tools such as chromogenic medium Baird-Parker agar, Electronic RapIDTM Staph Plus Code Compendium Panel System (ERIC®) Dryspot Staphytect Plus and Penicillin Binding Protein (PBP2') Plus assays; as well as, studying the susceptibility of isolates to different selected antibiotics. The r