Artificial intelligence (AI) has made deep inroads into dentistry in the last few years. The aim of this systematic review was to identify the development of AI applications that are widely employed in dentistry and evaluate their performance in terms of diagnosis, clinical decision-making, and predicting the prognosis of the treatment. The literature for this paper was identified and selected by performing a thorough search in the electronic data bases like PubMed, Medline, Embase, Cochrane, Google scholar, Scopus, Web of science, and Saudi digital library published over the past two decades (January 2000–March 15, 2020).After applying inclusion and exclusion criteria, 43 articles were read in full and critically analyzed. Quality analysis was performed using QUADAS-2. AI technologies are widely implemented in a wide range of dentistry specialties. Most of the documented work is focused on AI models that rely on convolutional neural networks (CNNs) and artificial neural networks (ANNs). These AI models have been used in detection and diagnosis of dental caries, vertical root fractures, apical lesions, salivary gland diseases, maxillary sinusitis, maxillofacial cysts, cervical lymph nodes metastasis, osteoporosis, cancerous lesions, alveolar bone loss, predicting orthodontic extractions, need for orthodontic treatments, cephalometric analysis, age and gender determination. These studies indicate that the performance of an AI based automated system is excellent. They mimic the precision and accuracy of trained specialists, in some studies it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.

Oral cancer (OC) is a deadly disease with a high mortality and complex etiology. Artificial intelligence (AI) is one of the outstanding innovations in technology used in dental science. This paper intends to report on the application and performance of AI in diagnosis and predicting the occurrence of OC. In this study, we carried out data search through an electronic search in several renowned databases, which mainly included PubMed, Google Scholar, Scopus, Embase, Cochrane, Web of Science, and the Saudi Digital Library for articles that were published between January 2000 to March 2021. We included 16 articles that met the eligibility criteria and were critically analyzed using QUADAS-2. AI can precisely analyze an enormous dataset of images (fluorescent, hyperspectral, cytology, CT images, etc.) to diagnose OC. AI can accurately predict the occurrence of OC, as compared to conventional methods, by analyzing predisposing factors like age, gender, tobacco habits, and bio-markers. The precision and accuracy of AI in diagnosis as well as predicting the occurrence are higher than the current, existing clinical strategies, as well as conventional statistics like cox regression analysis and logistic regression.

In the global epidemic era, oral problems significantly impact a major population of children. The key to a child’s optimal health is early diagnosis, prevention, and treatment of these disorders. In recent years, the field of artificial intelligence (AI) has seen tremendous pace and progress. As a result, AI’s infiltration is witnessed even in those areas that were traditionally thought to be best left to human specialists. The ultimate ability to improve patient care and make precise diagnoses of illnesses has revolutionized the world of healthcare. In the field of dentistry, the competence to execute treatment measures while still providing appropriate patient behavior counseling is in high demand, particularly in the field of pediatric dental care. As a result, we decided to conduct this review specifically to examine the applications of AI models in pediatric dentistry. A comprehensive search of the subjects was done using a wide range of databases to look for studies that have been published in peer-reviewed journals from its inception until 31 December 2022. After the application of the criteria, only 25 of the 351 articles were taken into consideration for this review. According to the literature, AI is frequently used in pediatric dentistry for the purpose of making an accurate diagnosis and assisting clinicians, dentists, and pediatric dentists in clinical decision making, developing preventive strategies, and establishing an appropriate treatment plan.

The objective of this paper was to evaluate the studies that have reported on psychological issues among dental students in Saudi Arabia and to develop coping strategies to overcome these mental health-related issues. The present systematic review is in accordance with the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search for the articles was carried out in the electronic databases by four independent researchers. The data search was performed in the electronic search engines like PubMed, Google Scholar, Web of Science, Scopus, Medline, Embase, Cochrane and Saudi Digital Library for scientific research articles published from January 2000 until December 2020. STROBE guidelines were adopted for qualitative analysis of six articles which met the eligibility criteria. The analysis of the literature revealed that most of the studies included were conducted in the past 8 years in different regions of Saudi Arabia. Findings of this systematic review clearly state that dental students in Saudi Arabia experience higher levels of depression, stress and anxiety and stress during their education period, with a higher stress for female students compared to male students. There is an urgent need to introduce interventional programs and preventive strategies to overcome the long-term effects.

Objective: To demonstrate the levels of parathyroid hormone secretion and genetic expressions of parathyroid hormone (PTH) and PTH1 receptor (PTH1R) genes in the dental pulp stem cells (DPSCs) from different age groups before and after induction of osteogenic differentiation. In addition, we also wanted to check their correlation with the degree of osteogenic differentiation. Methods: Human primary DPSCs from three age groups (milk tooth (SHEDs), 7–12 years old; young DPSCs (yDPSCs), 20–40 years old; old DPSCs (oDPSCs), 60+ years old) were characterized for mesenchymal stem cell (MSC) markers. DPSCs were subjected to osteogenic differentiation and functional staining. Gene expression levels were analyzed by qRT-PCR. Surface receptor analysis was done by flow cytometry. Comparative protein levels were evaluated by ELISA. Results: All SHEDs, yDPSCs, and oDPSCs were found to be expressing mesenchymal stem cell markers. SHEDs showed more mineralization than yDPSCs and oDPSCs after osteogenic induction. SHEDs exhibited higher expression of PTH and PTH1R before and after osteogenic induction, and after osteogenic induction, SHEDs showed more expression for RUNX2, ALPL, and OCN. Higher levels of PTH were observed in SHEDs and yDPSCs, and the number of PTH1R positive cells was relatively lower in yDPSCs and oDPSCs than in SHEDs. After osteogenic induction, SHEDs were superior in the secretion of OPG, and the secretions of ALPL and PTH and the number of PTH1R positive cells were relatively low in the oDPSCs. Conclusions: The therapeutic quality of dental pulp stem cells is largely based on their ability to retain their stemness characteristics. This study emphasizes the criterion of aging, which affects the secretion of PTH by these cells, which in turn attenuates their osteogenic potential.

The aim of this study was to assess the knowledge, attitudes, and practices of school teachers toward oral health. Descriptive study. School teachers (n = 150) of Davangere city were recruited into this study. The subjects completed a questionnaire that aimed to evaluate teachers’ knowledge, attitudes, and practices on oral health. The results were statistically analyzed and percentage was calculated. The participants’ oral hygiene habits were found to be regular. The majority of teachers showed good knowledge on oral health. Most of the teachers in this study recognized the importance of oral health. The majority of teachers did incorporate the importance of oral health in teaching and educating children in the school. But, not all teachers are involved effectively. So, the teachers should be trained comprehensively regarding importance of oral health and creating awareness on oral health promotion for their students in combination with health care personnel. Maganur PC, Satish V, Marwah N, Vishwas TD, Dayanand MC. Knowledge, Attitudes, and Practices of School Teachers toward Oral Health in Davangere, India. Int J Clin Pediatr Dent 2017;10(1):89-95.