Artificial intelligence applications and ethical challenges in oral and maxillo-facial cosmetic surgery: a narrative review

Artificial Intelligence Used for Diagnosis in Facial Deformities: A Systematic Review

AI is included in a lot of different systems. In facial surgery, there are some AI-based software programs oriented to diagnosis in facial surgery. This study aims to evaluate the capacity and training of models for diagnosis of dentofacial deformities in class II and class III patients using artificial intelligence and the potential use for indicating orthognathic surgery. The search strategy is from 1943 to April 2024 in PubMed, Embase, Scopus, Lilacs, and Web of Science. Studies that used imaging to assess anatomical structures, airway volume, and craniofacial positions using the AI algorithm in the human population were included. The methodological quality of the studies was assessed using the Effective Public Health Practice Project instrument. The systematic search identified 697 articles. Eight studies were obtained for descriptive analysis after exclusion according to our inclusion and exclusion criteria. All studies were retrospective in design. A total of 5552 subjects with an age range between 14.7 and 56 years were obtained; 2474 (44.56%) subjects were male, and 3078 (55.43%) were female. Six studies were analyzed using 2D imaging and obtained highly accurate results in diagnosing skeletal features and determining the need for orthognathic surgery, and two studies used 3D imaging for measurement and diagnosis. Limitations of the studies such as age, diagnosis in facial deformity, and the included variables were observed. Concerning the overall analysis bias, six studies were at moderate risk due to weak study designs, while two were at high risk of bias. We can conclude that, with the few articles included, using AI-based software allows for some craniometric recognition and measurements to determine the diagnosis of facial deformities using mainly 2D analysis. However, it is necessary to perform studies based on three-dimensional images, increase the sample size, and train models in different populations to ensure accuracy of AI applications in this field. After that, the models can be trained for dentofacial diagnosis.

Predicting optimal patient-specific postoperative facial landmarks for patients with craniomaxillofacial deformities

Orthognathic surgery primarily corrects skeletal anomalies and malocclusion to enhance facial aesthetics, aiming for an improved facial appearance. However, this traditional skeletal-driven approach may result in undesirable residual asymmetry. To address this issue, a soft tissue-driven planning methodology has been proposed. This technique estimates bone movements based on the envisioned optimal facial appearance, thereby enhancing surgical accuracy and effectiveness. This study investigates the initial implementation phase of the soft tissue-driven approach, simulating the patient's ideal appearance by realigning distorted facial landmarks to an ideal state. The algorithm employs symmetrization and weighted optimization strategies, aligning projected optimal landmarks with standard cephalometric values for both facial symmetry and form, which are essential in orthognathic surgery for facial aesthetics. It also incorporates regularization to preserve the patient's facial characteristics. Validation through retrospective analysis of preoperative patients and normal subjects demonstrates this method's efficacy in achieving facial symmetry, particularly in the lower face, and promoting a natural, harmonious contour. Adhering to soft tissue-driven principles, this novel approach shows promise in surpassing traditional methods, potentially leading to enhanced facial outcomes and patient satisfaction in orthognathic surgery.

The evolution of robotics: research and application progress of dental implant robotic systems

The use of robots to augment human capabilities and assist in work has long been an aspiration. Robotics has been developing since the 1960s when the first industrial robot was introduced. As technology has advanced, robotic-assisted surgery has shown numerous advantages, including more precision, efficiency, minimal invasiveness, and safety than is possible with conventional techniques, which are research hotspots and cutting-edge trends. This article reviewed the history of medical robot development and seminal research papers about current research progress. Taking the autonomous dental implant robotic system as an example, the advantages and prospects of medical robotic systems would be discussed which would provide a reference for future research.

The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey

Artificial intelligence (AI) approaches have been introduced in various disciplines but remain rather unused in head and neck (H&N) cancers. This survey aimed to infer the current applications of and attitudes toward AI in the multidisciplinary care of H&N cancers. From November 2020 to June 2022, a web-based questionnaire examining the relationship between AI usage and professionals' demographics and attitudes was delivered to different professionals involved in H&N cancers through social media and mailing lists. A total of 139 professionals completed the questionnaire. Only 49.7% of the respondents reported having experience with AI. The most frequent AI users were radiologists (66.2%). Significant predictors of AI use were primary specialty (V = 0.455; p < 0.001), academic qualification and age. AI's potential was seen in the improvement of diagnostic accuracy (72%), surgical planning (64.7%), treatment selection (57.6%), risk assessment (50.4%) and the prediction of complications (45.3%). Among participants, 42.7% had significant concerns over AI use, with the most frequent being the 'loss of control' (27.6%) and 'diagnostic errors' (57.0%). This survey reveals limited engagement with AI in multidisciplinary H&N cancer care, highlighting the need for broader implementation and further studies to explore its acceptance and benefits.

The future of artificial intelligence in facial plastic surgery

The role of artificial intelligence is emergent in facial plastic surgery. It offers specialists a potentially precise and efficient method of understanding our technical skills and pathways, and their impacts on patient outcomes and error rates. Algorithms have given life to personalised pre-operative assessment, surgical planning and outcome simulation, and post-operative monitoring. Despite these benefits, limitations at this time include the ethical acquisition of large datasets, biases produced by human input and trust in novel technologies. Careful consideration should be given to the role artificial intelligence may play in shaping the patient-surgeon relationship in the near future.

Artificial Intelligence in Facial Plastic and Reconstructive Surgery: A Systematic Review

Artificial intelligence (AI) is a technology that is evolving rapidly and is changing the world and medicine as we know it. After reviewing the PROSPERO database of systematic reviews, there is no article related to this topic in facial plastic and reconstructive surgery. The objective of this article was to review the literature regarding AI applications in facial plastic and reconstructive surgery.A systematic review of the literature about AI in facial plastic and reconstructive surgery using the following keywords: Artificial Intelligence, robotics, plastic surgery procedures, and surgery plastic and the following databases: PubMed, SCOPUS, Embase, BVS, and LILACS. The inclusion criteria were articles about AI in facial plastic and reconstructive surgery. Articles written in a language other than English and Spanish were excluded. In total, 17 articles about AI in facial plastic met the inclusion criteria; after eliminating the duplicated papers and applying the exclusion criteria, these articles were reviewed thoroughly. The leading type of AI used in these articles was computer vision, explicitly using models of convolutional neural networks to objectively compare the preoperative with the postoperative state in multiple interventions such as facial lifting and facial transgender surgery.In conclusion, AI is a rapidly evolving technology, and it could significantly impact the treatment of patients in facial plastic and reconstructive surgery. Legislation and regulations are developing slower than this technology. It is imperative to learn about this topic as soon as possible and that all stakeholders proactively promote discussions about ethical and regulatory dilemmas.

Artificial Intelligence in Plastic Surgery: Insights from Plastic Surgeons, Education Integration, ChatGPT's Survey Predictions, and the Path Forward

Background

Artificial intelligence (AI) is emerging as a transformative technology with potential applications in various plastic surgery procedures and plastic surgery education. This article examines the views of plastic surgeons and residents on the role of AI in the field of plastic surgery.

Methods

A 34-question survey on AI's role in plastic surgery was distributed to 564 plastic surgeons worldwide, and we received responses from 153 (26.77%) with the majority from Latin America. The survey explored various aspects such as current AI experience, attitudes toward AI, data sources, ethical considerations, and future prospects of AI in plastic surgery and education. Predictions from AI using ChatGPT for each question were compared with the actual survey responses.

Results

The study found that most participants had little or no prior AI experience. Although some believed AI could enhance accuracy and visualization, opinions on its impact on surgical time, patient recovery, and satisfaction were mixed. Concerns included patient privacy, data security, costs, and informed consent. Valuable AI training data sources were identified, and there was agreement on the importance of standards and transparency. Respondents expected AI's increasing role in reconstructive and aesthetic surgery, suggesting its integration into residency programs, addressing administrative challenges, and patient complications. Confidence in the enduring importance of human professionals was expressed, with interest in further AI research.

Conclusion

The survey's findings underscore the need to harness AI's potential while preserving human professionals' roles through informed consent, standardization, and AI education in plastic surgery.

Predicting Optimal Patient-Specific Postoperative Facial Landmarks for Patients with Craniomaxillofacial Deformities

Orthognathic surgery traditionally focuses on correcting skeletal abnormalities and malocclusion, with the expectation that an optimal facial appearance will naturally follow. However, this skeletal-driven approach can lead to undesirable facial aesthetics and residual asymmetry. To address these issues, a soft-tissue-driven planning method has been proposed. This innovative method bases bone movement estimates on the targeted ideal facial appearance, thus increasing the surgical plan's accuracy and effectiveness. This study explores the initial phase of implementing a soft-tissue-driven approach, simulating the patient's optimal facial look by repositioning deformed facial landmarks to an ideal state. The algorithm incorporates symmetrization and weighted optimization strategies, aligning projected optimal landmarks with standard cephalometric values for both facial symmetry and form, which are integral to facial aesthetics in orthognathic surgery. It also includes regularization to preserve the patient's original facial characteristics. Validated using retrospective analysis of data from both preoperative patients and normal subjects, this approach effectively achieves not only facial symmetry, particularly in the lower face, but also a more natural and normalized facial form. This novel approach, aligning with soft-tissue-driven planning principles, shows promise in surpassing traditional methods, potentially leading to enhanced facial outcomes and patient satisfaction in orthognathic surgery.

Application possibilities of artificial intelligence in facial vascularized composite allotransplantation-a narrative review

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surgery that represents a dogmatic shift in the surgical treatment of patients with severe facial disfigurements. While conventional reconstructive strategies were previously considered the goldstandard for patients with devastating facial trauma, FVCA has demonstrated promising short- and long-term outcomes. Yet, there remain several obstacles that complicate the integration of FVCA procedures into the standard workflow for facial trauma patients. Artificial intelligence (AI) has been shown to provide targeted and resource-effective solutions for persisting clinical challenges in various specialties. However, there is a paucity of studies elucidating the combination of FVCA and AI to overcome such hurdles. Here, we delineate the application possibilities of AI in the field of FVCA and discuss the use of AI technology for FVCA outcome simulation, diagnosis and prediction of rejection episodes, and malignancy screening. This line of research may serve as a fundament for future studies linking these two revolutionary biotechnologies.

Face the Future-Artificial Intelligence in Oral and Maxillofacial Surgery

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.

Using Generative Artificial Intelligence Tools in Cosmetic Surgery: A Study on Rhinoplasty, Facelifts, and Blepharoplasty Procedures

Artificial intelligence (AI), notably Generative Adversarial Networks, has the potential to transform medical and patient education. Leveraging GANs in medical fields, especially cosmetic surgery, provides a plethora of benefits, including upholding patient confidentiality, ensuring broad exposure to diverse patient scenarios, and democratizing medical education. This study investigated the capacity of AI models, DALL-E 2, Midjourney, and Blue Willow, to generate realistic images pertinent to cosmetic surgery. We combined the generative powers of ChatGPT-4 and Google's BARD with these GANs to produce images of various noses, faces, and eyelids. Four board-certified plastic surgeons evaluated the generated images, eliminating the need for real patient photographs. Notably, generated images predominantly showcased female faces with lighter skin tones, lacking representation of males, older women, and those with a body mass index above 20. The integration of AI in cosmetic surgery offers enhanced patient education and training but demands careful and ethical incorporation to ensure comprehensive representation and uphold medical standards.

Contemporary Role and Applications of Artificial Intelligence in Dentistry

Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to improve the quality of patient care and treatment outcomes while minimizing the risk of human error. Artificial Intelligence (AI) is transforming the dental industry, just like it is revolutionizing other sectors. It is used in dentistry to diagnose dental diseases and provide treatment recommendations. Dental professionals are increasingly relying on AI technology to assist in diagnosis, clinical decision-making, treatment planning, and prognosis prediction across ten dental specialties. One of the most significant advantages of AI in dentistry is its ability to analyze vast amounts of data quickly and accurately, providing dental professionals with valuable insights to enhance their decision-making processes. The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties; dental public health, endodontics, oral and maxillofacial surgery, oral medicine and pathology, oral & maxillofacial radiology, orthodontics and dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, and digital dentistry in general. We will also show the pros and cons of using AI in all dental specialties in different ways. Finally, we will present the limitations of using AI in dentistry, which made it incapable of replacing dental personnel, and dentists, who should consider AI a complimentary benefit and not a threat.

ChatGPT in Dentistry: A Comprehensive Review

Chat generative pre-trained transformer (ChatGPT) is an artificial intelligence chatbot that uses natural language processing that can respond to human input in a conversational manner. ChatGPT has numerous applications in the health care system including dentistry; it is used in diagnoses and for assessing disease risk and scheduling appointments. It also has a role in scientific research. In the dental field, it has provided many benefits such as detecting dental and maxillofacial abnormalities on panoramic radiographs and identifying different dental restorations. Therefore, it helps in decreasing the workload. But even with these benefits, one should take into consideration the risks and limitations of this chatbot. Few articles mentioned the use of ChatGPT in dentistry. This comprehensive review represents data collected from 66 relevant articles using PubMed and Google Scholar as databases. This review aims to discuss all relevant published articles on the use of ChatGPT in dentistry.