Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty‐two full‐text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty‐two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time‐saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state‐of‐the‐art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

BACKGROUND: E-learning is increasingly used during the COVID-19 pandemic, however the impact of this change on students is not known. This study aimed to evaluate perception and satisfaction of health sciences students towards E-learning during the COVID-19 lockdown. METHODS: A structured questionnaire was distributed to 2000 health care students either through email or social media platforms. The questionnaire was divided into two sections: the first section addressed demographic information such as age, education level, course of study, number of lectures attended and country. The second section gathered information on perception and satisfaction of students using 13 close-ended questions. Frequencies and percentages were assessed for demographic data, perception and satisfaction level of students. The paired sample t-test, independent t test and Spearman correlation were applied to evaluate statistical significance between different variables of the study. A p-value of <0.05 was considered significant. RESULTS: Data from 1255 participants were included at a response rate of 66.4%. More than one third (37%) of the students took 25 or more online E-learning sessions and 47% preferred Zoom as an online platform. Participants belonged to 11 countries from developed and developing nations. 41% reported interference of E-learning due to network problems. 60% considered that clinical and practical skills are best learned in clinics and laboratories. More than one third of the students preferred classroom teaching and 34% of the students did not feel confident enough to take exit exams after E-learning sessions. CONCLUSION: E-learning satisfaction levels were better among developed countries (7.34) compared to developing countries (5.82). The majority of participants agreed that E-learning was satisfactory in acquiring knowledge, however not effective in acquiring clinical and technical skills. As the COVID-19 lockdown eases, there is a need for improvement in the methods employed in E-learning and more blended learning among healthcare students is recommended.

The objective of this study was to investigate general dentists’ observations of various aesthetic dental procedures among social media users. A cross-sectional study was conducted at the Department of Prosthodontics, Altamash Institute of Dental Medicine, over a duration of six months. Data were collected using a well-structured questionnaire comprising 21 predefined responses. The questionnaire was uploaded and disseminated through Google Surveys by forwarding web page links through emails and WhatsApp. The data collected were analysed through Statistical Package for Social Sciences (SPSS-Version 25). The majority (90.7%) of the dental practitioners surveyed believed that there is an increase in the demand for aesthetic dental procedures and social media is a major contributor to it. Moreover, most of the 377 (81.8%) participants agreed that social media is a beneficial platform enabling them to educate, advertise, and communicate with patients. Concerning popular aesthetic procedures, teeth whitening (54.7%), Hollywood smile (17.1%), dental veneers (11.9%), and Invisalign (10.4%) were the most commonly demanded aesthetic procedures. The patients showed desire for these procedures because they were trending on social media platforms. Almost half of the general dental practitioners used social media to post their content related to aesthetic dentistry and to promote their work. They preferred using before and after pictures (48.6%) for advertising their content related to aesthetic dentistry. Within the limitations of the study, it is concluded that the demand for aesthetic dentistry is rapidly growing, and social media is the main driving force behind this revolution as the general population has direct access to the profiles of celebrities and influencers, who all appear to have ‘the perfect smile’. This shift in people’s self-image has created a surge in patients seeking cosmetic treatments.

The world is currently facing a pandemic crisis due to a novel coronavirus. For this purpose, acquiring updated knowledge regarding prevention and disinfection during the current pandemic is necessary for every dental practitioner. In our study, we aimed to evaluate globally the level of knowledge and the attitude of dental practitioners related to disinfection. A total of 385 participants out of 401 participants from 23 different countries across the world were included in the final analysis after the exclusion of incomplete responses. The majority of the dentists who responded were females (53.8%) and were practicing at private health institutes (36.4%). The mean knowledge score of the participants was estimated to be 4.19 ± 1.88 out of 12, reflecting insufficient knowledge, and the mean attitude score of the participants was estimated to be 12.24 ± 3.23 out of 15, which shows a positive attitude toward disinfection practices during coronavirus 2019 (COVID-19). Thus, the current study indicated a lack of knowledge in fundamental aspects of disinfection protocols with a significant and positive attitude from dental health professionals toward disinfection regarding the coronavirus 2019 (COVID-19) pandemic.

Objective. Analyzing and comparing the fit and accuracy of removable partial denture (RPDs) frameworks fabricated with CAD/CAM and rapid prototyping methods with conventional techniques. Materials and Methods. The present systematic review was carried out according to PRISMA guidelines. The search was carried out on PubMed/MEDLINE, Cochrane collaboration, Science direct, and Scopus scientific engines using selected MeSH keywords. The articles fulfilling the predefined selection criteria based on the fit and accuracy of removable partial denture (RPD) frameworks constructed from digital workflow (CAD/CAM; rapid prototyping) and conventional techniques were included. Results. Nine full‐text articles comprising 6 in vitro and 3 in vivo studies were included in this review. The digital RPDs were fabricated in all articles by CAD/CAM selective laser sintering and selective laser melting techniques. The articles that have used CAD/CAM and rapid prototyping technique demonstrated better fit and accuracy as compared to the RPDs fabricated through conventional techniques. The least gaps between the framework and cast (41.677 ± 15.546 μm) were found in RPDs constructed through digital CAD/CAM systems. Conclusion. A better accuracy was achieved using CAD/CAM and rapid prototyping techniques. The RPD frameworks fabricated by CAD/CAM and rapid prototyping techniques had clinically acceptable fit, superior precision, and better accuracy than conventionally fabricated RPD frameworks.

This study aimed to compare the surface roughness, hardness, and flexure strength of interim indirect resin restorations fabricated with CAD-CAM (CC), 3D printing (3D), and conventional techniques (CV). Twenty disk (3 mm × Ø10 mm) and ten bar specimens (25 × 2 × 2 mm) were fabricated for the CC, 3D, and CV groups, to be used for surface roughness, micro-hardness, and flexural strength testing using standardized protocol. Three indentations for Vickers micro-hardness (VHN) were performed on each disk and an average was identified for each specimen. Surface micro-roughness (Ra) was calculated in micrometers (μm) using a 3D optical non-contact surface microscope. A three-point bending test with a universal testing machine was utilized for assessing flexural strength. The load was applied at a crosshead speed of 3 mm/min over a distance of 25 mm until fracture. Means and standard deviations were compared using ANOVA and post hoc Tukey–Kramer tests, and a p-value of ≤0.05 was considered statistically significant. Ra was significantly different among the study groups (p < 0.05). Surface roughness among the CC and CV groups was statistically comparable (p > 0.05). However, 3D showed significantly higher Ra compared to CC and CV samples (p < 0.05). Micro-hardness was significantly higher in 3D samples (p < 0.05) compared to CC and CV specimens. In addition, CC and CV showed comparable micro-hardness (p > 0.05). A significant difference in flexural strength was observed among the study groups (p < 0.05). CC and 3D showed comparable strength outcomes (p > 0.05), although CV specimens showed significantly lower (p < 0.05) strength compared to CC and 3D samples. The 3D-printed provisional restorative resins showed flexural strength and micro-hardness comparable to CAD-CAM fabricated specimens, and surface micro-roughness for printed specimens was considerably higher compared to CAD-CAM and conventional fabrication techniques.