## 3 Results
### Artificial Intelligence and Robotics  
In addition to AR and VR, new technologies, such as AI and Robotics, have been applied in dentistry to improve the clinical practice [58]. AI is the ability of a machine to perform human tasks and revolves around its own intelligence to solve problems based on the learning of a specific set of data. AI refers to any machine or technology that can mimic human cognitive skills such as problem solving. The foundation of AI is to increase the ability of machines or its intelligence components to perform tasks with speed, low resources, accuracy, and precision. Machine learning is part of AI, which depends on algorithms to predict outcomes based on a dataset [59]. Algorithms are artificial neural networks, highly interconnected networks of computer processors inspired by biological nervous systems that function similarly to the human brain [60]. The most active areas of medical AI are diagnostics and prediction of prognoses. AI in the medical sector contributes significantly to helping decision making related to medical practice, while presenting a considerable level of potential for sound diagnosis and prediction [61; 62]. It was proven that machine learning, based on data derived from the decisions of dental professionals, achieved significant performance [63]. For example, different studies intended to generate caries prediction models to facilitate the likelihood calculation of an individual developing dental caries based on clinical findings or demographic and lifestyle factors [63; 64]. Another important feature is data mining, whose strength lies in the ability of finding causal relationships and comparisons that are innate in existing data [65]. The observations were obtained by data mining analysis, while the only role of dental professional was to collect and tabulate the data. All the above studies proved the application of AI in the current dental field to diagnose and make prognoses through extraction of useful information from large amounts of medical records [65]. Again, data mining analysis performed on a bulk of restorative data of patients revealed that differences in the material of dental restorations serve as important factors determining the lifespan of a restoration [66]. Currently, studies applying machine learning based on artificial neural networks to dental treatment through analysis of dental magnetic resonance imaging, computed tomography, and cephalometric radiography are actively underway. AI-based systems are often used for designing software programs that try to simplify data management and diagnosis in dentistry. Mostly, they are clinical decision support systems that assist and guide experts to make better decisions [67] and aesthetic mock-up [68]. AI-based systems have been used for better diagnosis, treatment planning and for prognosis prediction. AI in dentistry started procuring its role with emergence of data computation and availability of large amounts of patient data. For instance, the information acquired by radiological exam can be analysed by an algorithm which may improve and help the diagnosis and treatment phases of oral pathology and disease in an automatic way [65]. Additionally, AI technology has demonstrated excellent results in the detection of dental caries [69; 70], diagnosing oral squamous cell carcinoma [71], and evaluation of the correct working length in endodontics [72; 73; 74]. In adjunct to AI, robotics can represent the next frontier of dentistry. Robotics has been added to medicine since 1992, but only in 2001, a human-controlled robot, remotely located, was able to remove a dental caries, perform an endodontic treatment and execute a crown and bridge preparation [75]. In 2017, [PERSON] et al. demonstrated that robots' tooth preparation skills, such as laminate veneer and crowns preparations, are as accurate as those of human dentists [76]. Recently, a mobile wire-bending machine was introduced, which is capable of creating a fixed orthodontic retainer wire by means of intraoral scan data in only four minutes [77].