Artificial intelligence in Dental Implant Digital Workflow

The term 'artificial intelligence' (AI) refers to the idea of machines being capable of performing human tasks(McCarthy, 1989). A branch of AI is machine learning (ML), which 'learns' intrinsic statistical patterns (algorithms) in data to eventually make predictions on unseen data. Deep learning is a ML technique using multi-layer mathematical operations for learning and inferring on complex data like imagery(Kolossváry et al., 2019). Neural networks (NNs) are popular type of ML model which are highly interconnected networks of computer processors inspired by biological nervous systems. These systems may help connect dental professionals all over the world. The term “deep learning” is a reference to deep (multilayered) NN architectures. These are particularly useful for complex data structures, as they are capable of representing an image and its features such as edges, corners, shapes, and macroscopic patterns(Schwendicke et al., 2020). NNs are able to approximate any function and map any input to a given output. If a sufficiently large amount of data and computational resources are available. During the training process, data points and corresponding labels or numerical results are repetitively passed through the NN, A trained NN can predict the outcome of unseen data by passing the new data point through the network. Several types of deep neural networks are used, recurrent neural networks (RNNs) and convolutional neural networks (CNNs). RNNs deal with sequential input data, including speech and language. CNNs are specialized to deal with data with a grid-like topology, such as 2D and 3D images(Yasaka et al., 2018). Deep learning algorithms or convolutional neural networks (CNN) are rapidly emerging in the field of dentomaxillofacial (Leite et al., 2020). CNNs are designed to learn patterns from large datasets, without the need for a supervisor labeling the data. The term “deep” refers to the number of (hidden) network layers to progressively extract information and features from the input data. The layers are interconnected via nodes or neurons. Each hidden layer uses the output of the previous layer as its input, thereby increases the complexity and detail of what it is learning from layer to layer(Pesapane et al., 2018). CNNs have shown highly promising results in diagnosis and classification of diseases, such as caries staging, root fracture detection, cancer screening and diagnosis of periodontal disease. Moreover, AI applications are highly time-saving in preoperative treatment planning in implantology, orthodontics, and orthognathic surgery, by automated detection and segmentation of anatomical structures. Furthermore, they allow efficient and precise evaluation of treatment outcomes and can help us towards highly accurate prediction of diseases(Vranckx et al., 2020). The revolution in the restorative and prosthetic dentistry made with using cone-beam computed tomography (CBCT) and computer aided design computer aided manufacturing technology (CAD-CAM) to increase the accuracy of the prosthesis (Albdour et al., 2018). Moreover, 3D-printing is increasingly gaining ground, allowing patient-customized guided surgery Furthermore, recent innovations like virtual and augmented reality created new visualization systems for anatomic exploration(Farronato et al., 2019), Dentists in the process leverage their training and experience, learn from mistakes and patient feedback only to enhance the practice of dentistry over the years. After all this, the rate of misdiagnosis is quite significant if machines were to be taught to do what dentists learn over these years it will be easy for transmission of knowledge , standardization and improving treatment quality of patients all over the world. The market demand for dental implants is growing significantly the main problem is that results obtained from real cases shows some dental implants do not lead to success Using all these technologies with innovation of generative adversarial networks, laboratories are using AI to automatically generate advanced dental implant planning to achieve the best design of the final prosthesis to ensure perfect fit and ideal function while exceeding aesthetic expectations.