# Diagnostic Accuracy and Agreement Between AI and Clinicians in Orthodontic 3D Model Analysis
## 1 Introduction  
In recent years, advances in digital dentistry have led to the increasing use of intraoral scanners in clinical practice. Compared to conventional impression techniques, these scanners enable faster, more comfortable, and highly accurate data acquisition. They also facilitate orthodontic diagnosis and treatment planning by allowing for the rapid andseamless transfer of digital data, instant access to patient records, and a reduced need for physical storage [1; 2]. Alongside these developments, the integration of digital technologies into orthodontics has enabled more sophisticated planning tools. Digital software platforms now allow for the simulation and visualization of treatment outcomes in three dimensions, significantly enhancing the precision of diagnosis and treatment planning [3]. These tools rely heavily on the digital models produced by intraoral scanners, underscoring the critical role of accurate digital impressions in modern orthodontic workflows. In this context, clear aligner systems have emerged as a popular orthodontic treatment modality that aligns with the capabilities of digital workflows. They not only meet patients' aesthetic expectations but also offer enhanced comfort, reduced pain compared to fixed appliances, and fewer clinical appointments [4; 5]. The effectiveness of these systems depends on precise digital analysis and planning, which are made possible through the combined use of advanced scanning and modeling technologies. With recent developments in computer technology, artificial intelligence (AI) has increasingly been integrated into the medical field [6; 7; 8]. In orthodontics, AI has been applied to various tasks, including digital model analysis, malocclusion classification, anatomical landmark identification, prediction of post-treatment facial changes, classification based on clinical photographs, and tooth segmentation [9; 10; 11; 12; 13; 14; 15]. Comprehensive diagnosis and treatment planning are essential for successful orthodontic outcomes. Model analysis plays a central role in this process, incorporating evaluations such as space analysis, Bolton analysis, Angle classification, and overjet and overjet measurements [16]. Space analysis is a fundamental diagnostic parameter in orthodontics, traditionally performed by comparing the total mesiodistal widths of the teeth to the arch length. In digital models, the arch length is often defined as the curved distance measured along a digitally constructed arch form extending from the mesial surface of the right first molar to that of the left first molar [17]. The construction of this curve may be subject to variation due to subjective interpretation. This analysis reveals the relationship between required and available space, helping determine whether the teeth can be properly aligned. It is a fundamental mathematical equation that can directly influence decisions regarding extraction or non-extraction treatments [18]. Bolton analysis evaluates the mesiodistal tooth size ratio between the maxillary and mandibular teeth [19]. Even if ideal occlusion (in terms of cusp fossa relationships, overjet, and overbite) is present, minor spacing or crowding in one arch may indicate a Bolton discrepancy [20]. This analysis helps identify the amount of tooth size excess or deficiency in each arch, guiding the necessary corrections to achieve a Class I molar relationship and ideal occlusion [21]. Overjet is defined as the horizontal distance from the incisal edge of the maxillary central incisor to the labial surface of the mandibular incisor, measured parallel to the occlusal plane. Overbite is the vertical distance between the incisal edges of the upper and lower central incisors [20]. These parameters assess the antero-posterior and vertical relationships in the anterior region and are essential for identifying esthetic and functional problems. They serve as key references for accurate diagnosis and effective treatment planning [22].