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作 者:陈泽涛[1] 陈卓凡[2] Chen Zetao;Chen Zhuofan(Department of Oral Implantology,Hospital of Stomatology,Guanghua School of Stomatology,Sun Yat-sen University&Guangdong Provincial Key Laboratory of Stomatology,Guangzhou 510055,China;Clinic of Zhujiang New Town,Hospital of Stomatology,Guanghua School of Stomatology,Sun Yat-sen University&Guangdong Provincial Key Laboratory of Stomatology,Guangzhou 510623,China)
机构地区:[1]中山大学附属口腔医院种植科·中山大学光华口腔医学院·广东省口腔医学重点实验室,广州510055 [2]中山大学附属口腔医院珠江新城门诊·中山大学光华口腔医学院·广东省口腔医学重点实验室,广州510623
出 处:《中华口腔医学杂志》2024年第11期1094-1100,共7页Chinese Journal of Stomatology
基 金:广州市科技计划(2023B03J1232)。
摘 要:自主式口腔种植手术机器人已能实现手术操作智能, 然而口腔种植人工智能(AI)决策仍未实现。结合口腔种植临床诊疗流程、决策指标数据特征及人群相关指标分布特点, 在构建口腔种植AI决策系统的过程中, 存在以下五大关键难点, 分别为口腔种植专病标注数据库构建、种植定量指标预测、三维图像处理、指标数据不平衡的解决以及临床路径中多性质多模态指标的共同输出。本文结合实践经验和国内外研究现状, 分别阐述口腔种植AI决策系统构建的发展现状及难点问题, 以期为后续口腔种植AI决策建设提供参考。The oral implant surgery robot could achieved basic"surgical operation intelligence";however,"decision-making artificial intelligence"has not yet been achieved.The author previously discussed the specific concept of decision-making artificial intelligence.During our exploration of decision-making artificial intelligence,our team further integrated the clinical diagnosis and treatment process of oral implantation,along with the data characteristics of decision indicators and the distribution characteristics of demographic information.As a result,we identified five key scientific and technological issues in the process of decision-making artificial intelligence,namely the construction of a specialized annotation database for oral implantation,the prediction of quantitative indicators,the application of three-dimensional imaging,the solution of data imbalance within indicators,and the joint output of multi-property and multimodal indicators in clinical pathways.This paper will review artificial intelligence research in oral implantology and our team′s research progress,elaborating on the aforementioned challenges in intelligentization.It aims to provide references for addressing the mentioned scientific issues and guiding future research directions in the construction of decision-making artificial intelligence in oral medicine.
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