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Artificial intelligence (AI) has emerged as a versatile health-technology tool revolutionizing medical services through the implementation of predictive, preventative, individualized, and participatory approaches. AI encompasses different computational concepts such as machine learning, deep learning techniques, and neural networks. AI also presents a broad platform for improving preoperative planning, intraoperative workflow, and postoperative patient outcomes in the field of oral and maxillofacial surgery (OMFS). The purpose of this review is to present a comprehensive summary of the existing scientific knowledge. The authors thoroughly reviewed English-language PubMed/MEDLINE and Embase papers from their establishment to 1 December 2022. The search terms were (1) "OMFS" OR "oral and maxillofacial" OR "oral and maxillofacial surgery" OR "oral surgery" AND (2) "AI" OR "artificial intelligence". The search format was tailored to each database's syntax. To find pertinent material, each retrieved article and systematic review's reference list was thoroughly examined. According to the literature, AI is already being used in certain areas of OMFS, such as radiographic image quality improvement, diagnosis of cysts and tumors, and localization of cephalometric landmarks. Through additional research, it may be possible to provide practitioners in numerous disciplines with additional assistance to enhance preoperative planning, intraoperative screening, and postoperative monitoring. Overall, AI carries promising potential to advance the field of OMFS and generate novel solution possibilities for persisting clinical challenges. Herein, this review provides a comprehensive summary of AI in OMFS and sheds light on future research efforts. Further, the advanced analysis of complex medical imaging data can support surgeons in preoperative assessments, virtual surgical simulations, and individualized treatment strategies. AI also assists surgeons during intraoperative decision-making by offering immediate feedback and guidance to enhance surgical accuracy and reduce complication rates, for instance by predicting the risk of bleeding.

Background: When a patient receives a transplant-be it classically an organ or bone marrow or, more recently, composite allotransplantations of the limb or face-it can result in artificial chimerism. Such chimerism raises considerations in forensic medicine, a field that relies on the collection and identification of biological samples from crime scenes. Beyond this chimerism, composite allotransplantations create further challenges., Methods: After screening the literature and press releases, we provide a brief history and summary of some of the technologies used in forensic identification, explaining their advantages and pitfalls in the light of transplantation and cautioning against misidentifying those who evade justice by taking advantage of such considerations., Results: With face transplantation, patients can receive the skin, hair, salivary glands, teeth, and oral and nasal mucosa of their donors, components which hold great importance in forensic science. Modern technologies such as computer-assisted facial recognition, although gradually becoming more accurate over time, also face new challenges in this post-transplantation era as facial recognition software can be misled by surgical alterations of the face or face transplantation. With limb transplantation, there is an impact on fingerprint identification., Conclusions: Both surgical transplantation techniques and forensic technologies have seen incomprehensibly great innovation in the past century. Given the growing rate of successful composite transplantation in the USA and worldwide, it is now important for law enforcement agents to be aware of the new possibility of having two sets of genetic material, hair, saliva, fingerprints, or even facial recognition data for the same individual.

Background: Orthognathic surgery (OS) is a frequently performed procedure for the correction of dentofacial deformities and malocclusion. Research on OS is mostly limited to single-surgeon experience or single-institutional reports. We, therefore, retrospectively analyzed a multi-institutional database to investigate outcomes of OS and identify risk factors for peri- and postoperative complications., Methods: We reviewed the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2008-2020) to identify patients who underwent OS for mandibular and maxillary hypo- and hyperplasia. The postoperative outcomes of interest included 30-day surgical and medical complications, reoperation, readmission, and mortality. We also evaluated risk factors for complications., Results: The study population included 674 patients, 48% of whom underwent single jaw surgery, 40% double jaw surgery, and 5.5% triple jaw surgery. The average age was 29 ± 11 years, with an equal gender distribution (females: n = 336; 50%, males: n = 338; 50%). Adverse events were relatively rare, with a total of 29 (4.3%) complications reported. The most common surgical complication was superficial incisional infection (n = 14; 2.1%). While the multivariable analysis revealed isolated single lower jaw surgery ( p = 0.03) to be independently associated with surgical complication occurrence, it also identified an association between the outpatient setting and the frequency of surgical complications ( p = 0.03) and readmissions ( p = 0.02). In addition, Asian ethnicity was identified as a risk factor for bleeding ( p = 0.003) and readmission ( p = 0.0009)., Conclusion: Based on the information recorded by the ACS-NSQIP database, our analysis underscored the positive (short-term) safety profile of OS. We found OS of the mandible to be associated with higher complication rates. The calculated risk role of OS in the outpatient setting warrants further investigation. A significant correlation between Asian OS patients and postoperative adverse events was found. Implementation of these novel risk factors into the surgical workflow may help facial surgeons refine their patient selection and improve patient outcomes. Future studies are needed to investigate the causal relationships of the observed statistical correlations.

Background: Obstructive sleep apnea (OSA) is a chronic disorder of the upper airway. OSA surgery has oftentimes been researched based on the outcomes of single-institutional facilities. We retrospectively analyzed a multi-institutional national database to investigate the outcomes of OSA surgery and identify risk factors for complications. Methods: We reviewed the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database (2008−2020) to identify patients who underwent OSA surgery. The postoperative outcomes of interest included 30-day surgical and medical complications, reoperation, readmission, and mortality. Additionally, we assessed risk-associated factors for complications, including comorbidities and preoperative blood values. Results: The study population included 4662 patients. Obesity (n = 2909; 63%) and hypertension (n = 1435; 31%) were the most frequent comorbidities. While two (0.04%) deaths were reported within the 30-day postoperative period, the total complication rate was 6.3% (n = 292). Increased BMI (p = 0.01), male sex (p = 0.03), history of diabetes (p = 0.002), hypertension requiring treatment (p = 0.03), inpatient setting (p < 0.0001), and American Society of Anesthesiology (ASA) physical status classification scores ≥ 4 (p < 0.0001) were identified as risk-associated factors for any postoperative complications. Increased alkaline phosphatase (ALP) was identified as a risk-associated factor for the occurrence of any complications (p = 0.02) and medical complications (p = 0.001). Conclusions: OSA surgery outcomes were analyzed at the national level, with complications shown to depend on AP levels, male gender, extreme BMI, and diabetes mellitus. While OSA surgery has demonstrated an overall positive safety profile, the implementation of these novel risk-associated variables into the perioperative workflow may further enhance patient care.

Background: Reliable, time- and cost-effective, and clinician-friendly diagnostic tools are cornerstones in facial palsy (FP) patient management. Different automated FP grading systems have been developed but revealed persisting downsides such as insufficient accuracy and cost-intensive hardware. We aimed to overcome these barriers and programmed an automated grading system for FP patients utilizing the House and Brackmann scale (HBS)., Methods: Image datasets of 86 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2017 and May 2021, were used to train the neural network and evaluate its accuracy. Nine facial poses per patient were analyzed by the algorithm., Results: The algorithm showed an accuracy of 100%. Oversampling did not result in altered outcomes, while the direct form displayed superior accuracy levels when compared to the modular classification form (n = 86; 100% vs. 99%). The Early Fusion technique was linked to improved accuracy outcomes in comparison to the Late Fusion and sequential method (n = 86; 100% vs. 96% vs. 97%)., Conclusions: Our automated FP grading system combines high-level accuracy with cost- and time-effectiveness. Our algorithm may accelerate the grading process in FP patients and facilitate the FP surgeon's workflow.