The emergence of the novel virus severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causing coronavirus disease (COVID‐19) has led to a global pandemic and one of the most significant challenges to the healthcare profession. Dental practices are focal points for cross‐infection, and care must be taken to minimise the risk of infection to, from, or between dental care professionals and patients. The COVID‐19 epidemiological and clinical characteristics are still being collated but children's symptoms seem to be milder than those that adults experience. It is unknown whether certain groups, for example children with comorbidities, might be at a higher risk of more severe illness. Emerging data on disease spread in children, affected by COVID‐19, have not been presented in detail. The purpose of this article was to report current data on the paediatric population affected with COVID‐19 and highlight considerations for dentists providing care for children during this pandemic. All members of the dental team have a professional responsibility to keep themselves informed of current guidance and be vigilant in updating themselves as recommendations are changing so quickly.

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.

This study evaluated the efficacy of virtual reality (VR) distraction and counter-stimulation (CS) on dental anxiety and pain perception to local anesthesia in children. A prospective, randomized, single-blinded interventional clinical trial with a parallel design was used. Seventy children 7-11 years old who required local anesthesia (LA) for pulp therapy or tooth extraction were recruited and allocated to two groups with equal distribution based on the intervention. Group CS (n = 35) received CS and Group VR (n = 35) received VR distraction with ANTVR glasses. Anxiety levels (using pulse rate) were evaluated before, during, and after administration of local anesthesia, while pain perception was assessed immediately after the injection. Wong-Baker faces pain-rating scale (WBFPS), visual analog scale (VAS), and Venham's clinical anxiety rating scale (VCARS) were used for pain evaluation. Student's t-test was used to test the mean difference between groups, and repeated measures ANOVA was used to test the mean difference of pulse rates. Significant differences in mean pulse rates were observed in both groups, while children in the VR group had a higher reduction (P < 0.05), and the mean VCARS scores were significant in the VR group (P < 0.05). Mean WBFPS scores showed less pain perception to LA needle prick in the CS group while the same change was observed in the VR group with VAS scores. VR distraction is better than CS for reducing anxiety to injection in children undergoing extraction and pulpectomy.

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.