Silver nanoparticles have been a recent focus of many researchers in dentistry, and their potential uses and benefits have drawn attention in dentistry and medicine. The fabrication and utilization of nanoscale substances and structures are at the core of the rapidly developing areas of nanotechnology. They are often used in the dental industry because they prevent bacteria from making nanoparticles, oxides, and biofilms. They also stop the metabolism of bacteria. Silver nanoparticles (AgNPs) are a type of zero-dimensional material with different shapes. Dentistry has to keep up with changing patient needs and new technology. Silver nanoparticles (AgNPs) can be used in dentistry for disinfection and preventing infections in the oral cavity. One of the most interesting metallic nanoparticles used in biomedical applications is silver nanoparticles (AgNPs). The dental field has found promising uses for silver nanoparticles (AgNPs) in the elimination of plaque and tartar, as well as the elimination of bacterial and fungal infections in the mouth. The incorporation of AgNPs into dental materials has been shown to significantly enhance patients’ oral health, leading to their widespread use. This review focuses on AgNP synthesis, chemical properties, biocompatibility, uses in various dental fields, and biomaterials used in dentistry. With an emphasis on aspects related to the inclusion of silver nanoparticles, this descriptive review paper also intends to address the recent developments of AgNPs in dentistry.

Artificial intelligence (AI) is an area of computer science that focuses on designing machines or systems that can perform operations that would typically need human intelligence. AI is a rapidly developing technology that has grabbed the interest of researchers from all across the globe in the healthcare industry. Advancements in machine learning and data analysis have revolutionized oral health diagnosis, treatment, and management, making it a transformative force in healthcare, particularly in dentistry. Particularly in dentistry, AI is becoming increasingly prevalent as it contributes to the diagnosis of oro-facial diseases, offers treatment modalities, and manages practice in the dental operatory. All dental disciplines, including oral medicine, operative dentistry, pediatric dentistry, periodontology, orthodontics, oral and maxillofacial surgery, prosthodontics, and forensic odontology, have adopted AI. The majority of AI applications in dentistry are for diagnoses based on radiographic or optical images, while other tasks are less applicable due to constraints such as data availability, uniformity, and computational power. Evidence-based dentistry is considered the gold standard for decision making by dental professionals, while AI machine learning models learn from human expertise. Dentistry AI and technology systems can provide numerous benefits, such as improved diagnosis accuracy and increased administrative task efficiency. Dental practices are already implementing various AI applications, such as imaging and diagnosis, treatment planning, robotics and automation, augmented and virtual reality, data analysis and predictive analytics, and administrative support. The dentistry field has extensively used artificial intelligence to assist less-skilled practitioners in reaching a more precise diagnosis. These AI models effectively recognize and classify patients with various oro-facial problems into different risk categories, both individually and on a group basis. The objective of this descriptive review is to review the most recent developments of AI in the field of dentistry.

Background: The recent outbreak of coronavirus (COVID-19) caused a significant impact on dentistry. It is imperative to have sufficient knowledge of COVID-19 to manage patients in the dental operatory. Aim: To assess the knowledge and perceptions of dentists from different specialities about COVID-19 disease. Settings and Design: Cross-sectional online survey. Materials and Methods: This study used a descriptive cross-sectional study design with a self-administered questionnaire. The questionnaire included three sets of 23 questions [Demographic-4; Source of information-1; Knowledge-10 and Perceptions-8]. The comparison of mean scores of knowledge and perceptions were interpreted based on the occupation of dental specialists. Statistical Analysis Used: The association between demographic variables and dental specialists’ knowledge and perception scores was carried out using SPSS (Version IBM 21.0, NY, USA). Results: A total of 429 dentists from various specialties participated in the present study. The study had obtained a overall good knowledge score (92.7%) with a mean value of 8.86 + 0.22, and a perception score (70.7%) with a mean value of 5.4+0.3. The present study reports a statistically significant difference between age (p=0.03) and knowledge source (p< 0.05). The multi variate regression analysis showed that dentists’ specialty had no significant effect on knowledge and perception. Conclusion: The study reports sufficient knowledge and perception scores. Oral maxillofacial surgeons showed higher knowledge scores, while prosthodontics and periodontics achieved good mean scores for perception on COVID-19. Social media and health authorities played an equally important role in the overall knowledge of the source of information related to COVID-19.