AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR DIAGNOSIS OF DEEP BITE IN CHILDREN.

Deep bite is one of the most common dental anomalies in children and adolescents. Timely and accurate diagnosis of this pathology is crucial for selecting the optimal orthodontic treatment strategy and preventing the development of functional and morphological disorders. The aim of this study is to develop and clinically test an algorithm for diagnosing deep bite in children using artificial intelligence technologies. The study utilized clinical, anthropometric, photometric, and radiographic examination methods, as well as computer analysis of teleradiographs and digital dental models. The proposed AI algorithm automated the analysis of diagnostic data, increased the accuracy of deep bite determination, and optimized orthodontic treatment planning. The use of intelligent diagnostic systems helps reduce inter-clinical variability and improve the effectiveness of orthodontic care for children.深覆颌（Deep bite）是儿童及青少年最为常见的牙齿异常病症之一。对该病症开展及时且精准的诊断，对于遴选最优正畸治疗策略、预防功能与形态障碍的发生具有关键意义。本研究旨在开发并临床验证一种依托人工智能技术的儿童深覆颌诊断算法。研究采用临床检查、人体测量学检测、光度测量法及放射学检查手段，同时对头颅定位放射片（teleradiographs）与数字化牙模进行计算机分析。所提出的人工智能算法实现了诊断数据分析的自动化，提升了深覆颌判定的准确性，并优化了正畸治疗规划流程。智能诊断系统的应用有助于降低临床间诊疗差异，提升儿童正畸诊疗的有效性。