Application of Artificial Intelligence in Different Fields of Oromaxillofacial Surgery

Abstract

Aim The mechanization of today’s world and the recent developments about robots and its use in industry and medicine, as well as the replacement by these tools instead of human labor with the ability to make them intelligent, have made artificial intelligence (AI) and robots hot topics these days. Artificial intelligence is the ability of intelligent machines to predict unknown variables by using algorithms and internal statistical patterns and information structures. In the structure of AI, which are divided into two general categories, machine learning and deep learning, human neural patterns are in the form of neural networks. The working areas of AI in maxillofacial and plastic surgery are wide and in the fields of rhinoplasty, orthognathic surgery, cleft lip and palate, augmentation in implants, and diagnosis and determination of survival rate in cancer patients. In this review article the different functions of AI in the fields of maxillofacial surgery and the extent of its effectiveness in helping to improve the acceleration of work are discussed.  Methods & Materials This study examines articles from 2000–2023. Google Scholar and PubMed databases were used for searching and keywords such as artificial intelligence-machine learning, deep learning were investigated. The inclusion criteria for this study were all the articles that were written and reviewed in the years in question, in English, and the field of research was maxillofacial or plastic surgery. Results Rhinoplasty: The application of artificial intelligence (AI) in the field of examining bone shape, examining the beauty of patients based on the evaluation of pre-treatment photographs and predicting the results of the operation based on radiographic interpretation. Orthognathic surgery: AI can be used in the field of lateral cephalometric tracing, scanning of patients’ occlusion, examination of periodontal diseases and dental problems, as well as making oral appliances and predicting the operation using machine learning (ML). Cleft palate and lip: Examining the success rate of bone grafting in the alveolar cleft area and predicting the results of grafting and the risk of infection and failure of grafting in the area is one of the applications of AI in this field. Oral cancer: Oral squamous cell cancer is one of the most common head and neck cancers and due to the high rate of recurrence, morbidity and mortality, it is of great concern in medical sciences today. The application of AI and the interpretation of risk factors and samples using complex neural algorithms can reduce the mortality rate through faster disease prediction and at earlier stages. Conclusion In this review article, the applications of AI and its sub-branches, including ML, deep learning, in various branches of maxillofacial surgery, including orthognathics, rhinoplasty, cleft lip and palate, and oral cancer are discussed. Making decisions smarter by using complex neural algorithms and its involvement in decisions can reduce human errors and increase patient satisfaction.