Eliana Dantas Costa, José Andery Carneiro, Breno Augusto Guerra Zancan, Hugo Gaêta-Araujo, C. Oliveira-Santos, Alessandra Alaniz Macedo, Camila Tirapelli
{"title":"人工智能生成蛀牙、缺失牙和修复牙健康研究报告的潜力","authors":"Eliana Dantas Costa, José Andery Carneiro, Breno Augusto Guerra Zancan, Hugo Gaêta-Araujo, C. Oliveira-Santos, Alessandra Alaniz Macedo, Camila Tirapelli","doi":"10.15517/ijds.2024.59184","DOIUrl":null,"url":null,"abstract":"This study aims to indicate the potential of artificial intelligence (AI) in epidemiological reports of decayed, missed and restored teeth. As a proof of concept our study model used panoramic x-ray images and an AI algorithm for tooth numbering, detection of the caries and restorations with accuracy over 80% for such diagnostic tasks. The output came as the number of decayed, missed and restored teeth according to patient´s age and the DMFT index (number of decayed, missing, and filled teeth) which varied from 3.6 (up to 20 years old) to 20.4 (+60 years old). Thus, it is suggested that AI is a promising method to automate health data collection through the analysis of x-rays.","PeriodicalId":509192,"journal":{"name":"Odovtos - International Journal of Dental Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Potential of Artificial Intelligence to Generate Health Research Reports of Decayed, Missed and Restored Teeth\",\"authors\":\"Eliana Dantas Costa, José Andery Carneiro, Breno Augusto Guerra Zancan, Hugo Gaêta-Araujo, C. Oliveira-Santos, Alessandra Alaniz Macedo, Camila Tirapelli\",\"doi\":\"10.15517/ijds.2024.59184\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to indicate the potential of artificial intelligence (AI) in epidemiological reports of decayed, missed and restored teeth. As a proof of concept our study model used panoramic x-ray images and an AI algorithm for tooth numbering, detection of the caries and restorations with accuracy over 80% for such diagnostic tasks. The output came as the number of decayed, missed and restored teeth according to patient´s age and the DMFT index (number of decayed, missing, and filled teeth) which varied from 3.6 (up to 20 years old) to 20.4 (+60 years old). Thus, it is suggested that AI is a promising method to automate health data collection through the analysis of x-rays.\",\"PeriodicalId\":509192,\"journal\":{\"name\":\"Odovtos - International Journal of Dental Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Odovtos - International Journal of Dental Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15517/ijds.2024.59184\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Odovtos - International Journal of Dental Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15517/ijds.2024.59184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
这项研究旨在说明人工智能（AI）在龋齿、缺失牙和修复牙流行病学报告中的潜力。作为概念验证，我们的研究模型使用全景 X 光图像和人工智能算法进行牙齿编号、龋齿检测和修复，此类诊断任务的准确率超过 80%。根据患者的年龄和 DMFT 指数（蛀牙、缺失牙和填充牙的数量），输出结果为蛀牙、缺失牙和修复牙的数量，DMFT 指数从 3.6（20 岁以下）到 20.4（60 岁以上）不等。因此，人工智能是通过分析 X 光片自动收集健康数据的一种可行方法。
Potential of Artificial Intelligence to Generate Health Research Reports of Decayed, Missed and Restored Teeth
This study aims to indicate the potential of artificial intelligence (AI) in epidemiological reports of decayed, missed and restored teeth. As a proof of concept our study model used panoramic x-ray images and an AI algorithm for tooth numbering, detection of the caries and restorations with accuracy over 80% for such diagnostic tasks. The output came as the number of decayed, missed and restored teeth according to patient´s age and the DMFT index (number of decayed, missing, and filled teeth) which varied from 3.6 (up to 20 years old) to 20.4 (+60 years old). Thus, it is suggested that AI is a promising method to automate health data collection through the analysis of x-rays.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
