Applications of artificial intelligence and machine learning in orthognathic surgery: A scoping review

Mohaideen, Kaja; Negi, Anurag; Verma, Dinesh Kumar; Kumar, Neeraj; Sennimalai, Karthik; Negi, Amita

doi:10.1016/j.jormas.2022.06.027

Cited by 25 publications

(4 citation statements)

References 38 publications

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“…An orthognathic surgeon's clinical experience is essential to creating a detailed treatment plan, and the plan plays a vital role in the outcome [17]. As a surgeon designs and fabricates surgical splints based on CT (computed tomography scan) or CBCT (Cone-beam computed tomography systems) models, 3D craniomaxillofacial features are automatically registered [18,19].…”

Section: Orthognathic Surgeriesmentioning

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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Section: Orthognathic Surgeriesmentioning

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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“…AI refers to the capability of a computer system to accurately interpret and learn from external data and to flexibly adapt obtained knowledge to execute specific tasks. The remarkable advancements in computational functions related to the rise of big data over the past five decades have propelled the application of AI into new domains [9]. For example, AI is available for face and voice recognition, among other new technologies.…”

Section: Introductionmentioning

confidence: 99%

A Review of Artificial Intelligence in Breast Imaging

Al-Karawi,

Al-Zaidi,

Helael

et al. 2024

Tomography

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With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women’s physical and mental health. Early breast cancer screening—through mammography, ultrasound, or magnetic resonance imaging (MRI)—can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI.

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“…Several AI-based software programs are used in maxillofacial surgery to process images (intraoral scans, 3D photographs, and tomographic images) for treatment planning and outcomes prediction [ 5 ]; however, clinical experience is needed to train machine learning based on craniomaxillofacial features and to corroborate the craniometric landmark or measurements, as well as the number and direction of hard and soft tissue movements required for the surgical treatment [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

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

Ravelo,

Acero,

Fuentes-Zambrano

et al. 2024

JPM

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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

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Applications of artificial intelligence and machine learning in orthognathic surgery: A scoping review

Cited by 25 publications

References 38 publications

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

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

A Review of Artificial Intelligence in Breast Imaging

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

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