Artificial intelligence for oral and maxillo-facial surgery: A narrative review

Rasteau, Simon; Ernenwein, D.; Savoldelli, Charles; Boulétreau, P.

doi:10.1016/j.jormas.2022.01.010

Cited by 38 publications

(32 citation statements)

References 55 publications

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“…Representative articles are already reporting on AI algorithms aiding in diagnosis, therapeutic decision making, preoperative planning, and prediction and evaluation of outcomes. Thanks to their advanced classification, learning, prediction, and detection capabilities, AI algorithms complement human skills while minimizing their imperfections and inaccuracies [ 4 ]. Several of the registered studies reported preference for the use of AI in the detection of head and neck tumors using image data (radiographic, microscopic and ultrasonographic images) [ 2 , 23 , 60 , 104 , 105 ].…”

Section: Resultsmentioning

confidence: 99%

“…The tissue-prediction field needs more relevant 3D data and outputs, as the currently available data are a combination of different measurements, 2D and 3D planning, and imaging [ 48 ]. Significant investments are also being made by the industry in the research and development of applied AI to digital orthodontics and robotic surgery [ 4 , 108 ]. AI has the potential to be an immensely powerful tool in oral and maxillofacial surgery in the early future, and it is the responsibility of all maxillofacial surgeons to collect virtual data and to achieve a positive symbiosis with the clinical use of AI.…”

Section: Resultsmentioning

confidence: 99%

“…This may indicate that only the recent 3rd AI generation represents a mature technology with clinical impacts in dentistry. All modern progress and innovations in dentistry have been achieved due to the scientific approach that is currently experiencing a paradigm shift in the interdisciplinary relationship between AI and data science [ 4 , 5 ]. The recent boom is powered by major AI subfields, which include: Machine Learning (ML) Neural Networks (ANN) Computation Vision, Robotics Expert Systems Speech Processing Natural Language Processing …”

Section: Introductionmentioning

confidence: 99%

“…Recently, various valuable narrative reviews were published that concluded that the AI approach to imaging technology is profoundly changing the established protocols of diagnosis in dentistry [ 4 , 5 , 26 , 62 , 63 , 64 ]. The application of AI in healthcare is an area of significant attention and importance.…”

Section: Introductionmentioning

confidence: 99%

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Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

et al. 2022

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This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

et al. 2022

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“…Algorithms also support treatment decisions and preoperative procedures. Orthognathic surgery, oral cancerology, and oral surgery are fields where machine learning techniques are applied [10]. Moreover, AI models have been used to classify implants on radiographs, predict osteointegration success and peri-implantitis implant survival, and optimize implant design parameters such as porosity, length, and diameter to minimize stress at the implant-bone interface [10].…”

Section: Introductionmentioning

confidence: 99%

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

Rokhshad

Keyhan

Yousefi³

2023

Maxillofac Plast Reconstr Surg

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Artificial intelligence (AI) refers to using technologies to simulate human cognition to solve a specific problem. The rapid development of AI in the health sector has been attributed to the improvement of computing speed, exponential increase in data production, and routine data collection. In this paper, we review the current applications of AI for oral and maxillofacial (OMF) cosmetic surgery to provide surgeons with the fundamental technical elements needed to understand its potential. AI plays an increasingly important role in OMF cosmetic surgery in various settings, and its usage may raise ethical issues. In addition to machine learning algorithms (a subtype of AI), convolutional neural networks (a subtype of deep learning) are widely used in OMF cosmetic surgeries. Depending on their complexity, these networks can extract and process the elementary characteristics of an image. They are, therefore, commonly used in the diagnostic process for medical images and facial photos. AI algorithms have been used to assist surgeons with diagnosis, therapeutic decisions, preoperative planning, and outcome prediction and evaluation. AI algorithms complement human skills while minimizing shortcomings through their capabilities to learn, classify, predict, and detect. This algorithm should, however, be rigorously evaluated clinically, and a systematic ethical reflection should be conducted regarding data protection, diversity, and transparency. It is possible to revolutionize the practice of functional and aesthetic surgeries with 3D simulation models and AI models. Planning, decision-making, and evaluation during and after surgery can be improved with simulation systems. A surgical AI model can also perform time-consuming or challenging tasks for surgeons.

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