[Applications and perspectives of artificial intelligence in periodontology].

Chunxu Lü, Shaohua Ge
{"title":"[Applications and perspectives of artificial intelligence in periodontology].","authors":"Chunxu Lü, Shaohua Ge","doi":"10.7518/hxkq.2025.2025103","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) is rapidly advancing in periodontology, bringing new opportunities to clinical diagnosis, risk assessment, personalized treatment planning, and remote patient care. Leveraging core technologies such as deep learning, machine learning, and natural language processing, AI significantly enhances the sensitivity of early periodontal disease detection and provides precise quantification of alveolar bone loss and soft tissue damage. AI facilitates multimodal data integration by synthesizing medical history, lifestyle factors, and imaging data, thereby offering enhanced accurate risk prediction and personalized therapeutic recommendations. By integrating remote monitoring with tailored health counseling, AI helps patients maintain adherence to self-care protocols, significantly improving their oral health-related quality of life and treatment satisfaction. Moreover, AI demonstrates considerable potential in periodontal research and education, particularly in large-scale data mining, virtual clinical case simulations, and natural language processing-assisted literature management. Nevertheless, challenges remain concerning model generalizability, data quality, ethical concerns, and interpretability. The advancement of multi-center big-data platforms is expected to foster a profound integration of AI and periodontology, propelling precision medicine and digital healthcare, enabling holistic management from prevention to long-term care, and enhancing diagnostic efficiency and patient health outcomes.</p>","PeriodicalId":94028,"journal":{"name":"Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology","volume":"43 5","pages":"620-627"},"PeriodicalIF":0.0000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12573713/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7518/hxkq.2025.2025103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial intelligence (AI) is rapidly advancing in periodontology, bringing new opportunities to clinical diagnosis, risk assessment, personalized treatment planning, and remote patient care. Leveraging core technologies such as deep learning, machine learning, and natural language processing, AI significantly enhances the sensitivity of early periodontal disease detection and provides precise quantification of alveolar bone loss and soft tissue damage. AI facilitates multimodal data integration by synthesizing medical history, lifestyle factors, and imaging data, thereby offering enhanced accurate risk prediction and personalized therapeutic recommendations. By integrating remote monitoring with tailored health counseling, AI helps patients maintain adherence to self-care protocols, significantly improving their oral health-related quality of life and treatment satisfaction. Moreover, AI demonstrates considerable potential in periodontal research and education, particularly in large-scale data mining, virtual clinical case simulations, and natural language processing-assisted literature management. Nevertheless, challenges remain concerning model generalizability, data quality, ethical concerns, and interpretability. The advancement of multi-center big-data platforms is expected to foster a profound integration of AI and periodontology, propelling precision medicine and digital healthcare, enabling holistic management from prevention to long-term care, and enhancing diagnostic efficiency and patient health outcomes.

人工智能在牙周病中的应用与展望
人工智能(AI)正在牙周病学领域迅速发展,为临床诊断、风险评估、个性化治疗计划和远程患者护理带来了新的机遇。人工智能利用深度学习、机器学习、自然语言处理等核心技术,显著提高了牙周病早期检测的敏感性,并提供了牙槽骨丢失和软组织损伤的精确量化。人工智能通过综合病史、生活方式因素和影像数据,促进多模式数据整合,从而提供更准确的风险预测和个性化的治疗建议。通过将远程监控与量身定制的健康咨询相结合,AI帮助患者保持对自我保健方案的遵守,显著提高了口腔健康相关的生活质量和治疗满意度。此外,人工智能在牙周研究和教育方面显示出相当大的潜力,特别是在大规模数据挖掘、虚拟临床病例模拟和自然语言处理辅助文献管理方面。然而,挑战仍然存在于模型的普遍性、数据质量、伦理问题和可解释性方面。多中心大数据平台的发展有望促进人工智能与牙周病的深度融合,推动精准医疗和数字医疗,实现从预防到长期护理的整体管理,提高诊断效率和患者健康结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书