人工智能在牙科全景片分析中的应用：系统评价综述。
Applications of artificial intelligence in the analysis of dental panoramic radiographs: an overview of systematic reviews.
机构信息
Institute of Public Health, Jagiellonian University Medical College, Skawińska, Poland.
Department of Glass Technology and Amorphous Coatings, Faculty of Materials Science and Ceramics, AGH University of Science and Technology, Mickiewicza, Poland.
出版信息
Dentomaxillofac Radiol. 2023 Oct;52(7):20230284. doi: 10.1259/dmfr.20230284. Epub 2023 Sep 4.
OBJECTIVES
This overview of systematic reviews aimed to establish the current state of knowledge on the suitability of artificial intelligence (AI) in dental panoramic radiograph analysis and illustrate its changes over time.
METHODS
Medical databases covered by the Association for Computing Machinery, Bielefeld Academic Search Engine, Google Scholar, and PubMed engines were searched. The risk of bias was assessed using ROBIS tool. Ultimately, 12 articles were qualified for the qualitative synthesis. The results were visualized with timelines, tables, and charts.
RESULTS
In the years 1988-2023, a significant development of information technologies for the analysis of DPRs was observed. The latest analyzed AI models achieve high accuracy in detecting caries (91.5%), osteoporosis (89.29%), maxillary sinusitis (87.5%), periodontal bone loss (93.09%), and teeth identification and numbering (93.67%). The detection of periapical lesions is also characterized by high sensitivity (99.95%) and specificity (92%). However, due to the small number of heterogeneous source studies synthesized in systematic reviews, the results of this overview should be interpreted with caution.
CONCLUSION
Currently, AI applications can significantly support dentists in dental panoramic radiograph analysis. As systematic reviews on AI become outdated quickly, their regular updating is recommended. PROSPERO registration number: CRD42023416048.
目的
本系统评价综述旨在确定人工智能（AI）在口腔全景放射分析中的适用性的现有知识状态，并说明其随时间的变化。
方法
检索了由计算机协会、比勒费尔德学术搜索引擎、谷歌学术和 PubMed 引擎涵盖的医学数据库。使用 ROBIS 工具评估偏倚风险。最终，有 12 篇文章符合定性综合的条件。结果通过时间线、表格和图表进行可视化。
结果
在 1988 年至 2023 年期间，观察到用于 DPR 分析的信息技术的显著发展。最新分析的 AI 模型在检测龋齿（91.5%）、骨质疏松症（89.29%）、上颌窦炎（87.5%）、牙周骨丢失（93.09%）和牙齿识别和编号（93.67%）方面具有很高的准确性。根尖病变的检测也具有很高的灵敏度（99.95%）和特异性（92%）。然而，由于系统评价中综合的异质源研究数量较少，因此应谨慎解释本综述的结果。
结论
目前，人工智能应用可以极大地支持牙医进行口腔全景放射分析。由于关于 AI 的系统评价很快就会过时，因此建议定期更新。PROSPERO 注册号：CRD42023416048。
Zotero 插件