Ai cephalometric analysis Methods Twelve Traditional cephalometric radiographs depict a three-dimensional structure in a two-dimensional plane; therefore, errors may occur during a quantitative assessment. With the emergence of digital tools for cephalometric analysis such as OneCeph, WebCeph, and NemoCeph, there is growing interest in their reliability compared to traditional manual tracings. Given these recent developments in computing, such AI algorithms can be used for simple and complicated tasks and, consequently, show promise for various health care fields. Background: Artificial intelligence (AI) is revolutionizing cephalometric diagnosis in orthodontics, streamlining the patient assessments. 5 mm. Automated is an automated cephalometric analyzer developed by DDH Inc. Methods For AI Cephalometric tracing and analysis; AI CBCT Segmentation; Cancel Anytime. Search methods: An electronic search AI-driven automated lateral cephalometric tracing. Artificial intelligence can be used to enhance low-dose cone In the future, AI algorithms used for the automated localisation of cephalometric landmarks may be more accurate than manual analysis. We performed a systematic review and meta-analysis to assess the accuracy and underlying Objectives: To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according to the test style of the worldwide AI challenges at the International Symposium on Biomedical Imaging conferences held by the Institute of Electrical and Using AI to identify cephalometric landmarks is a great innovation in clinical practice. Automated cephalometric analysis is one of the major applications of artificial intelligence in the field of orthodontics. Objectives The aim of the present systematic review and meta-analysis is to assess the accuracy of automated landmarking using deep learning in comparison with manual tracing for cephalometric analysis of 3D medical In particular, automated cephalometric approaches have had some success in streamlining work and reducing inter-operator variability compared to manual landmark annotation in traditional cephalometric analysis [4,11]. 6 Despite the variety of applicable techniques for automated The aim of this paper was to present data from the literature on the effectiveness of AI in orthodontic diagnostics based on the analysis of lateral cephalometric radiographs. A step forward is constituted by fully automated AI-assisted cephalometric analysis, where the landmarks are automatically In computer-assisted cephalometric analysis, computerized cephalometric tracing programs, such as V Ceph (CyberMed, Inc. The objective of this article was to compare cephalometric measurements conducted by different specialists and systems tailored for such measurements, as well as to evaluate the capabilities of artificial intelligence in this field. , (2020) analyzed the accuracy of their AI for automated cephalometric analysis based on commonly used orthodontic parameters . Although there were several studies comparing the difference of cephalometric analysis between human and AI [16 Objectives To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according The AI-based cephalometric analysis provided comprehensive reports with over 100 measurements. After uploading thousands of cephalometric images to the computer database, the professor’s group at Seoul National University Dental Hospital (SNUDH) developed the program. To investigate the experience of respondents, the items in the third section focused on their For inclusion in the meta-analysis, the studies should present one of the following outcomes: (1) the proportion of cephalometric landmarks correctly identified with AI within the thresholds of 2 or 3 mm (agreement) and (2) the mean divergence between cephalometric landmarking with AI and manual landmarking, in millimeters. WebCeph is an innovative Aritificial Intelligence driven online orthodontic and orthognathic platform. Five questions on the fundamental knowledge of AI-assisted cephalometric analysis and other AI-based applications in orthodontics are provided to evaluate the respondents’ actual knowledge level (2 single-choice and 3 multiple-choice, nos. The analysis can be performed manually on acetate tracing sheets, digitally by manual selection of landmarks or by recently introduced Artificial Intelligence (AI)-driven tools or softwares that automatically detect landmarks and Therefore, an AI-based cephalometric analysis was implemented to increase the reliability of the study. Authors and year Aim Number of. This review aims to provide a comprehensive overview of the present state of AI applications in orthodontics, which can be categorized into the following domains: (1) diagnosis, including cephalometric analysis, dental analysis, facial analysis, skeletal-maturation-stage determination and upper-airway obstruction assessment; (2) treatment planning, including decision making Objectives: To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according to the test style of the worldwide AI challenges at the International Symposium on Biomedical Imaging conferences held by the Institute of Electrical and Purpose: The aim of this investigation was to create an automated cephalometric X‑ray analysis using a specialized artificial intelligence (AI) algorithm. The AI is a promising tool for facilitating cephalometric tracing in routine clinical practice as well as analyzing large databases for research purposes. This study used the initial cephalograms of 220 patients aged 18 years or older. Deep learning (DL) has been increasingly employed for automated landmark detection, e. CNN (U-Net) 100 Background Cephalometric analysis is essential in orthodontic diagnosis and treatment planning. Material and method: A total of 1500 lateral cephalometric films that met the inclusion criteria were classified as Class I, Class II, and Voxel3Di®'s Cephalo. The evolution from manual cephalometric analysis to AI-assisted cephalometric analysis is aimed at improving the diagnostic value by reducing measurement errors and saving clinical time [9,10 Table 3: Studies related to the application of AI for cephalometric analysis. 23–26 Unlike the time-consuming manual cephalometric analysis, AI can assess images within seconds, reducing the analysis time The results of automatic cephalometric analysis have proven to be relatively stable and repeatable, compared with the highly operator-dependent manual analysis with significant variability in landmark identification. WebCeph supports: Automatic cephalometric tracing, Cephalometric analysis, Visual treatment simulation, Automatic superimposition, Image archive and Photo gallery. WebCeph is an innovative Aritificial Intelligence driven online orthodontic and orthognathic platform. Only the hinge axis angle (HAA) and SDA showed significant (p = 0. However, to the best of our knowledge, few recent Fully automated AI-based analysis. The use of AI is prevalent in numerous aspects of daily life, and AI-based algorithms are now widely used in technology. Cephalometric Landmark Detection and Placement by Artificial Intelligence. Fast and accurate AI analysis on Lateral Cephalogram X-rays. 408 lateral cephalometries were This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and Recently, Artificial Intelligence (AI) has spread in orthodontics, in particular within cephalometric analysis, where computerized digital software is able to provide linear-angular measurements upon manual landmark identification. Articles with AI-based cephalometric analysis for landmark identification, Clinical trials, English language articles. 43%: The AI expert system could be used to automatically identify cephalometric landmarks with high accuracy immediately. This significantly improves Purpose The aim of this investigation was to evaluate the accuracy of various skeletal and dental cephalometric parameters as produced by different commercial providers that make use of artificial intelligence (AI)-assisted automated cephalometric analysis and to compare their quality to a gold standard established by orthodontic experts. Applications that use AI-based image analysis are becoming The accuracy of determining cephalometric landmarks using widely available commercial AI-based software and advanced AI algorithms was presented and discussed. In recent years, artificial intelligence technology has been used in the field of orthodontics. X-rays. Therefore, a cephalometric analysis using AI may replace a human analysis in the future. This study aimed to create an artificial intelligence (AI) model that uses cephalometric analysis measurements to accurately classify maxillofacial morphology, allowing for the standardization of maxillofacial morphology classification. Cephalometry is a crucial examination in orthodontic diagnostics and during the planning of orthognathic surgical procedures. Artificial Intelligence has created a huge impact in different areas of dentistry. The main objective of this study is to identify the artificial intelligence algorithms that yield the best results for Lin et al. This study Unpublished literature was searched electronically by keywords such as artificial intelligence and cephalometric landmarks, machine learning and cephalometric landmarks, and ‘automatic detection of cephalometric landmarks and orthodontics’. These days, it is extensively being used for cephalometric analysis. This study was done to evaluate the Five questions on the fundamental knowledge of AI-assisted cephalometric analysis and other AI-based applications in orthodontics are provided to evaluate the respondents’ actual knowledge level (2 single-choice and 3 multiple-choice, nos. With its advanced machine learning and computer vision algorithms, Cephalo. The fully-automatic method uses AI to trace, identify landmarks, and calculate the To evaluate the techniques used for the automatic digitization of cephalograms using artificial intelligence algorithms, highlighting the strengths and weaknesses of each one and In orthodontics, cephalometric analysis with the assistance of AI is applied to the evaluation of post-treatment results and prediction of growth [6,7,8]. 2020. The 2D Basic plan includes: 3 AI Ceph Tracing and It was estimated that the mean difference in a manual tracing of cephalometric landmarks by different orthodontists was 1. AI systems are being evaluated for their accuracy and efficiency compared to conventional methods performed by professionals. Methods: The CBCT scans (a field of view of 15 × 15 cm) used in the study were obtained from 30 consecutive patients, aged 18 to 50. Manual CA is time-consuming and prone to variability. The sequence of steps followed for the generation of the tracing reports for the fully automated AI-based cephalometric analysis briefly includes uploading to the online platform of the AI-based (WebCeph TM, Cephio, and Ceppro DDH Inc. Cephalometric measurements done using WebCeph and 3. The authors were able to show that, out of twelve different orthodontic parameters (including skeletal sagittal, skeletal vertical, and dental parameters), only one parameter was found to be significantly different compared to the On the other hand, cephalometric analysis using DL has been focused on at a rate of 22%, while AI in cephalometrics has been regarded by conventional works at a rate of 30%. A revision of the title is suggested. AI Cephalometric tracing and analysis; AI CBCT Segmentation; Cancel Anytime. Ai® is Artificial intelligence (AI) is revolutionizing cephalometric diagnosis in orthodontics, streamlining the patient assessments. Cephalometric analysis is required for precise orthodontic diagnosis and treatment planning; this commences with precise localization of cephalometric landmarks, and AI streamlines this process in a rapid and very consistent manner . Objectives: This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and three-dimensional (3D) cone-beam computed tomographic (CBCT) images. This study ai With these programs, automatic cephalometric analysis including diagnostic and analytical imaging tasks can be performed by AI and machine learning technologies. The 2D Basic plan includes: 3 AI Ceph Tracing and Analysis Cases per Month; Comprehensive AI Cephalometric Analysis Tools; Dedicated and Personalized Technical Support Background: Cephalometric analysis has been used as one of the main diagnostic tools for orthodontic diagnosis and treatment planning. The 2D Basic plan includes: 3 AI Ceph Tracing and Analysis Cases per Month; Comprehensive AI Cephalometric Analysis Tools; Dedicated and Personalized Technical Support Abstract Background. Dobratulin et al 11. The average time for downloading one result of the automated cephalometric analysis from the AI engine server to the client device was 48 ms. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. Yue W, Yin D, Li The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI-assisted cephalometric analysis platforms such as WebCeph, WeDoCeph, and CephX give rise to notable variation in accuracy and reliability compared to traditional manual digital tracing, specifically in terms of angular and linear measurements. To our knowledge, there are no published data comparing all the 4 systems: fully automated, computerized, app-aided, and manual tracing. The analysis of the agreement between repeated manual measurements and ABSTRACTObjectives. 8% were interested in future AI applications in orthodontics [13]. However, to the best of our knowledge, few recent studies about AI performance of cephalometric analysis which is useful for clinicians are available. AI alone is still not fully reliable at locating It remains uncertain whether artificial intelligence-based programs can detect cephalometric landmarks with accuracy. Products DentaliQ ortho – assists dentists and orthodontists in their daily routine with AI technology that automatically conducts a cephalometric analysis with 42 anatomical landmarks and 25 assessments. A digital or scanned cephalometric image is saved in the database and added by software in automated cephalometric analysis. This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on This narrative review is aimed at giving an outline of cephalometric analysis in orthodontics using AI. Artificial intelligence technology is at the forefront of these efforts. To investigate the experience of respondents, the items in the third section focused on their Machine learning (ML) is an artificial intelligence paradigm that enables computers to learn and improve from data without being explicitly programmed. To investigate the experience of respondents, the items in the third section Automatic cephalometric analysis. metric analysis and thus improve the accuracy of mea-surements and reduce errors due to clinician subjectivity [8]. Automated 2-D cephalometric analysis on X-ray images by a model-based approach. Ceppro is based on the latest statistical and computer technologies and demonstrates reliable performances in detecting 78 landmarks on cephalometric images, in analyzing various cephalometric variables, in As a result, various commercially available fully automated AI driven cephalometric analysis platforms like CephX®, CEFBOT and WebCeph™ have been developed. Review articles, letters to editors, gray literature, case reports, incomplete articles which showed only the abstract without a definitive comparison between AI and human examiners, articles in which there was no comparison of AI is a broad area that includes reasoning, typical linguistic dispensation, machine learning, and planning. Thus, from the analysis, it has been revealed that AI in cephalometrics has gained more attention in research than other considered concepts. 3D Analysis makes it easy for surgeons [] the field of cephalometric analysis is AI-assisted analysis using dedicated websites [22, 23, 26–31]. 2, 3, 4 The reliability of these AI . , 2001 [49] Aims to identify the landmarks on lateral cephalogram 20. Methods: This study aims to compare the accuracy and repeatability of CA results among three commercial AI-driven programs: CephX, WebCeph, and AudaxCeph. The rest of the cephalometric analyses showed no correlation with the NSD indicators. The systematic analysis of literature was carried out by performing an 1， The article focuses on the application of AI in cephalometric analysis. The 2D Basic plan includes: 3 AI Ceph Tracing and Analysis Cases per Month; Comprehensive AI Cephalometric Analysis Tools; Dedicated and Personalized Technical Support This study aimed to analyze the existing literature on how artificial intelligence is being used to support the identification of cephalometric landmarks. Sys-tematic and random errors are the most common types of errors in cephalometric analysis [19, 20]. To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according to the test style of the worldwide AI challenges at the International Symposium on Biomedical Imaging conferences held by the Institute of Electrical The AI-based cephalometric analysis provided comprehensive reports with over 100 measurements. 1. Ai® software is a cutting-edge AI cephalometric analysis software that offers instant digitization and analysis of dental radiographs. AI was not able to identify the various cephalometric landmarks with the same accuracy. The purpose of this study was to compare Cephalometric analysis is considered as an important tool that has been applied for diagnosis and treatment planning. These landmarks were re-identified by all examiners with the aid of AI. Latest algorithms are developing rapidly, and computational resources are increasing Fully automatic system for accurate localisation and analysis of cephalometric landmarks in lateral cephalograms The AI-based methods of cephalometric analysis can be semi-automatic or fully automatic. Various automated cephalometric software have been developed which utilizes artificial intelligence and claim to be reliable. 15 It involves the identification of anatomical anchor points on X-ray images, followed by the measurement of various distances, angles, and ratios for the clarification of the AI-based cephalogram is aimed at improving the diagnostic value of analysis by saving time and minimizing errors. ) software, selecting the custom analysis, and automatic tracing followed by AI Cephalometric tracing and analysis; AI CBCT Segmentation; Cancel Anytime. Cone beam computed tomography, on the other hand, minimizes image distortion, allowing essential areas to be observed without overlap. Multiple studies confirmed a wide range of software enabling recognition and detection and automatic placement of cephalometric landmarks, detecting pathologies using CBCT images, pathologies ranging from tumors, cysts, periapical lesions, caries, supernumerary teeth, tissue alterations as present in Cephalometric analysis can be used to analyze the facial skeleton, generally in a two-dimensional (2D) fashion and based on specialized lateral and anteroposterior (AP) skull radiographs (cephalograms). The 2D Basic plan includes: 3 AI Ceph Tracing and Analysis Cases per Month; Comprehensive AI Cephalometric Analysis Tools; Dedicated and Personalized Technical Support manual cephalometric analysis and AI based programs with WebCeph presenting the least duration and manual method showing highest duration. CNN: 400: Lateral Cephalometric Radiograph: 88. CellmatiQ and its AI-based automated Cephalometric Analysis were featured in the December 2019 issue (#6) of the Digital Dental Magazin. Therefore, this study aimed to compare the accuracy of manual cephalometric analyses to cephalometric analysis using AI, computerized method, and app-aided systems. Cephalometric analysis has been used as one of the main tools for orthodontic diagnosis and treatment planning. Conclusion: The cephalometric measurements obtained from both WebCeph and Cephio programs are highly accurate when compared to manual measurements. The aim was to assess the precision and accuracy of cephalometric analyses performed by artificial intelligence (AI) with and without human augmentation. At less than 30 cents per X-ray analysis (based on Lateral Cephalometric tracing), our software offers an affordable, high-value tool for dental professionals. conducted an online survey to assess the knowledge, attitude, and perception (KAP) of orthodontists for the use of AI in cephalometric analysis and concluded that 72. Discover the world's research 25+ million members Lateral cephalometric analysis continues to be one of the gold standard diagnostic aids in orthodontics, with various software available to enhance this. The use of cephalometric analysis is particularly justified when In the field of orthodontics, AI has been used to identify landmarks, and to aid diagnosis and data analysis . We compared the accuracy of this analysis to the current gold standard (analyses performed by human experts) to evaluate precision and clinical application of such an approach in orthodontic routine. A common ML model employs training data for learning by matching the input features to output labels. These AI systems have the potential to standardize access to orthodontic diagnostics, particularly benefiting resource-limited AI based landmark detection, analysis, and treatment simulation. In The latter operations are considered semi-automated cephalometric analysis. This review discusses the history, uses, and various methods of AI used for cephalometric In recent years, AI was employed to perform cephalometric analysis, which is supposed to relieve clinicians’ work and save time. After your free trial, you will be automatically subscribed to our 2D Basic Plan for just $69 per month. 7 In this paper we reported 6 articles that have applied AI based automated models for cephalometric analysis. Four dental professionals with varying experience levels identified 31 landmarks on 30 cephalometric radiographs twice. Despite the Background: Cephalometric analysis (CA) is an indispensable diagnostic tool in orthodontics for treatment planning and outcome assessment. This technique is specifically indicated for cases involving planned anteroposterior movements but is not necessary for all orthodontic treatments. The study assessed the accuracy of AI cephalometric analysis by changing the number of cephalograms available for the AI training from 50 to 2000 radiographs and the number of marked points in one picture from 19 to 80. The 3D cephalometric analysis was conducted using two methods. These results emphasize the importance of meticulous In line with the trend of comparing the performance of evolving AI, the purpose of this study was to compare and evaluate an automated cephalometric analysis, based on the latest deep learning method of automatically identifying cephalometric landmarks,4,6,19 with a number of previously published AIs. The analysis of the agreement between repeated manual measurements and The aim of the study was to assess the accuracy and efficiency of a new artificial intelligence (AI) method in performing lateral cephalometric radiographic measurements. 7% of respondents felt that AI can accurately perform cephalometric analysis and 88. The accuracy is also high for landmarks that have been considered difficult to estimate accurately in The use of AI is prevalent in numerous aspects of daily life, and AI-based algorithms are now widely used in technology. Identifies, annotates and traces orthodontic landmarks. The development of reliable and automated tools to detect and perform cephalometric analysis have great repercussion for the clinician as it On the AI engine server, the proposed algorithm automatically detected all 23 landmarks from one cephalogram in less than 0. 23–26 Unlike the time-consuming manual cephalometric analysis, AI can assess images within seconds, reducing the analysis time Lin et al. Even when the same individual evaluates the same image, variations in results AI Cephalometric tracing and analysis; AI CBCT Segmentation; Cancel Anytime. 039) negative correlations. TRY FREE CEPH. Since its introduction in 1931 by Broadbent, lateral cephalometric analysis has remained the main diagnostic procedure in orthodontics; this procedure plays a pivotal role in treatment planning. AI followed by manual tuning of the landmarks’ position might be an accurate method in lateral cephalometric analysis. 7–9,20,21 In addition, the study assessed how accurately the latest AI performed The focus of this study was to evaluate the accuracy and reproducibility of Webceph® (South Korea), an AI-web-based cephalometric analysis platform which can also be used as a smartphone application, and to compare it This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and three-dimensional (3D) cone-beam computed tomographic (CBCT) images. The major advantage of using these softwares is that multiple cephalometric analyses can be accomplished within seconds after digital cephalogram is uploaded. EAI Pathology. Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making - A The results of automatic cephalometric analysis have proven to be relatively stable and repeatable, compared with the highly operator-dependent manual analysis with significant variability in landmark identification. g. This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and Background: The aim of this study was to compare and evaluate three AI-assisted cephalometric analysis platforms-CephX, WeDoCeph, and WebCeph-with the traditional digital tracing method using NemoCeph software. Agreement: Brand-Altman analysis was performed to examine the agreement of cephalometric analysis values by AI. Computer-aided cephalometric analysis offers numer-ous benefits but is still dependent on human execution, which can be influenced by various individual factors such as eye fatigue, screen resolution, and the operator’s level of expertise The use of artificial intelligence in orthodontics is emerging as a tool for localizing cephalometric points in two-dimensional X-rays. In the area of medicine and dentistry, machine learning is currently the most widely used AI application. Identify, annotate and trace 150+ orthodontic landmarks in just 10 seconds. Artificial Intelligence Web-based Orthodontic and Orthognathic Platform. Given these recent developments in computing, Purpose The aim of this investigation was to create an automated cephalometric X‑ray analysis using a specialized artificial intelligence (AI) algorithm. 3D Analysis Advanced AI-Driven 3D Cephalometric Tracing and Analysis for Invivo 3D Analysis provides the most advanced orthodontic analysis tool on the market. Abstract. , Seoul, Korea), Rainbow Ceph (Dentium Co, Gyeonggi-do, Korea), and Dolphin ACDS is an AI-based software that provides automatic cephalometric landmark detection, cephalometric tracing, measurements, and cephalometric analysis. The 2D Basic plan includes: 3 AI Ceph Tracing and Purpose: The aim of this investigation was to create an automated cephalometric X‑ray analysis using a specialized artificial intelligence (AI) algorithm. Leveraging unique 3D tracing methods and machine learning users can create accurate and consistent tracings directly from CBCT scans with the click of a button*. , for cephalometric purposes. 16-20). 2， Please explain the inclusion and exclusion criteria for the literature search and the reason why the author only searched two databases, Fully automated AI-assisted cephalometric analysis of 13 lateral cephalograms were retrospectively compared to the cephalometric analysis performed twice by a blinded operator with a computerized Compared with traditional cephalometric analysis, AI landmark identification shows superiority in repeatability and efficiency [11, 15]. This study aimed to assess the reliability, accuracy, and time consumption of artificial intelligence (AI)-based software compared to a conventional digital cephalometric analysis method on 2D lateral cephalogram. Pathology Detection. Search methods: An electronic search With these programs, automatic cephalometric analysis including diagnostic and analytical imaging tasks can be performed by AI and machine learning technologies. Products. AI-driven automated lateral cephalometric tracing. Numerous reviews show promising results in the application of AI in the early prediction of treatment needs, in determining the demand for orthognathic surgery or tooth extraction, in predicting cephalometric landmarks on 2D or 3D radiographs, as well as in identifying maturational properties of a growing patient. 4 s on average. The analysis can be performed manually on acetate tracing sheets, digitally by manual selection of landmarks or by recently introduced Artificial Intelligence (AI)-driven tools or softwares that automatically detect landmarks and While manual annotation of landmarks serves as the current gold standard for cephalometric analysis, Therefore, there has been a growing interest in using artificial intelligence (AI), Kunz et al. The first method involved manual AI Cephalometric tracing and analysis; AI CBCT Segmentation; Cancel Anytime. Objectives To compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks (AI) with previously published AI according AI-driven automated lateral cephalometric tracing. To ensure the objectivity of cephalometric analysis, AI-based methods were used to compare and evaluate different images rather than relying on human assessment. 1. This narrative review is aimed at giving an outline of cephalometric analysis in orthodontics using AI. Automatic detection of anatomical reference points on radiological images of the head profile. Since most of the included studies' conclusions were based on a wrong 2 mm cut-off difference between the AI automatic landmark location and that allocated by human operators, future research should focus on refining the most powerful architectures to improve the clinical Objectives: This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and three-dimensional (3D) cone-beam computed tomographic (CBCT) images. Background: Cephalometric analysis (CA) is an indispensable diagnostic tool in orthodontics for treatment planning and outcome assessment. Therefore, theaim of this prospective study was to compare cephalometric Cephalometric analysis evaluates lateral skull radiographs obtained with a cephalostat to determine skeletal patterns and assess treatment complexity. knowledge of AI-assisted cephalometric analysis and other AI-based applications in orthodontics are provided to evaluate the respondents’ actual knowledge level (2 single-choice and 3 multiple-choice, #16 to #20). Russia. 3) Correlation: To investigate the influence of anterior–posterior and vertical Objectives: To compare 3D cephalometric analysis performed using AI with that conducted manually by a specialist orthodontist. 150+ Landmarks. Grau et al. ykucjmjb kprpd ntacmrb ceypaq gscly fzvi endu kfi eqahuz cubhj