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  1. Ahmed N, Halim MSB, Ghani ZA, Khan ZA, Abbasi MS, Jamayet NB, et al.
    Biomed Res Int, 2021;2021:6674400.
    PMID: 33969123 DOI: 10.1155/2021/6674400
    The objective of this paper was to evaluate the existence of golden percentage in natural maxillary anterior teeth with the aid of 3D digital dental models and 2D photographs. And to propose regional values of golden percentage for restoration of maxillary anterior teeth. For this purpose, one hundred and ninety dentate subjects with sound maxillary anterior teeth were selected. Standardized frontal images were captured with DSLR, and the apparent width of maxillary anterior teeth was measured utilizing a software on a personal laptop computer. Once the dimensions were recorded, the calculations were made according to the golden percentage theory (GPT). The data were analyzed by independent and paired T-test. The level of significance was set at p < 0.05. The golden percentage values were not found in this study. The values obtained were 16%, 15%, 20%, 20%, 15%, and 16% moving from the right canine to the left canine teeth. There was no significant gender difference in the golden percentage values. Thus, golden percentage should not be used solely for the correction of anterior teeth or for determining dental attractiveness. Emphasis should be given to a range of dental proportion on regional basis.
  2. Maqsood A, Sadiq MSK, Mirza D, Ahmed N, Lal A, Alam MK, et al.
    Biomed Res Int, 2021;2021:5437237.
    PMID: 34845437 DOI: 10.1155/2021/5437237
    Objective: The present study was aimed at assessing the impact of teledentistry, its application, and trends in uplifting dental practice and clinical care around the world. Material and Methods. The present observational study comprised of an electronic survey distributed among dental professionals around the globe. The validated survey form consisted of a total 26 questions with 5-point Likert scale response. The questionnaire used was divided into four domains: usefulness of teledentistry for patients, its usefulness in dental practice, its capacity to improve the existing practice, and the concerns attached to its use. The statistical analysis was performed using SPSS-25. ANOVA test was used to assess the effect of independent variables on dependent variables. A p value of ≤0.05 was taken as statistically significant.

    Results: A total of 506 dental professionals participated in the study with the response rate of 89.39%. More than half of the participants (50-75%) endorsed that teledentistry is a useful tool for improving clinical practice as well as patient care. Two-thirds of the participants (69.96%) considered that teledentistry would reduce cost for the dental practices. On the other hand, about 50-70% of dental professionals expressed their concerns regarding the security of the data and consent of patients. The most preferred communication tool for teledentistry was reported to be videoconference followed by phone. The majority of participants recommended the use of teledentistry in the specialty of oral medicine, operative dentistry, and periodontics. There was a significant difference between the age, experience of dentists, and their qualifications with domains of teledentistry.

    Conclusions: The overall impact of dental professionals towards teledentistry was positive with adequate willingness to incorporate this modality in their clinical practice. However, the perceived concerns pertaining to teledentistry are significant impediments towards its integration within the oral health system. An in-depth study of its business model and cost-benefit needs of time, especially in the context of developing countries, in order to avail the optimum benefits of teledentistry.

  3. Ahmed N, Abbasi MS, Zuberi F, Qamar W, Halim MSB, Maqsood A, et al.
    Biomed Res Int, 2021;2021:9751564.
    PMID: 34258283 DOI: 10.1155/2021/9751564
    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.

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