Yarlagadda Sri Kalyan, Samavati Navid, Ghorbanifarajzadeh Mina, Levinta Vlada, Sojoudi Alireza, Inam Wardah, Dolan Teresa A
Overjet, Inc., 2093 Philadelphia Pike #9194, Claymont, DE, 19703, USA.
Sci Rep. 2025 Jul 1;15(1):20398. doi: 10.1038/s41598-025-07484-7.
This research introduces Oral Score Basic (OS-B), a novel Artificial Intelligence (AI) derived methodology designed to provide a comprehensive, objective assessment of individual teeth and overall oral health, initially focused on dental conditions. Leveraging data from more than 340,000 patients across 2,558 U.S. dental practices, OS-B combines radiographic findings and periodontal probing depths with a treatment probability-weighted cost function to quantify the severity of dental conditions. The OS-B score aims to address limitations in prior oral health scoring systems by incorporating nuanced clinical data accounting for disease severity, and providing a scalable, data-driven approach to measuring oral health. This score was developed using Overjet's FDA-cleared AI platform, which detects dental conditions using bitewing and periapical radiographs, providing a detailed analysis of each tooth. OS-B's effectiveness was validated by demonstrating a strong correlation between tooth scores and treatment costs, surpassing the predictive power of previous scoring systems. This research presents a foundational framework for AI-enabled oral health scoring, with potential applications in value-based care, population risk analysis, and consumer health management. Future iterations may expand to include additional dimensions of oral health beyond clinical conditions such as risk factors and measures of oral function and esthetics, further enhancing the score's public health and clinical utility and patient engagement.
本研究引入了口腔评分基础版（OS-B），这是一种全新的人工智能（AI）衍生方法，旨在对单颗牙齿及整体口腔健康状况进行全面、客观的评估，最初侧重于牙齿疾病。OS-B利用来自美国2558家牙科诊所的34万多名患者的数据，将X光检查结果和牙周探诊深度与治疗概率加权成本函数相结合，以量化牙齿疾病的严重程度。OS-B评分旨在通过纳入考虑疾病严重程度的细微临床数据，并提供一种可扩展的、数据驱动的方法来衡量口腔健康，从而解决先前口腔健康评分系统的局限性。该评分是使用Overjet公司获得美国食品药品监督管理局（FDA）批准的人工智能平台开发的，该平台通过咬合翼片和根尖片检测牙齿疾病，对每颗牙齿进行详细分析。通过证明牙齿评分与治疗成本之间存在强相关性，OS-B的有效性得到了验证，其预测能力超过了先前的评分系统。本研究提出了一个基于人工智能的口腔健康评分基础框架，在基于价值的医疗、人群风险分析和消费者健康管理方面具有潜在应用。未来的迭代版本可能会扩展到纳入除临床状况之外的口腔健康其他维度，如风险因素以及口腔功能和美观度的衡量指标，进一步提高该评分在公共卫生和临床方面的实用性以及患者参与度。
