口腔种植决策的“类脑智能化”

"Brain⁃inspired intelligence"in dental implant decision⁃making

现阶段的种植手术机器人已基本实现“手术操作智能”,然而,机器人种植决策的“类脑智能”仍处于理论及探索阶段。临床种植方案制定取决于种植时机、种植区域、骨量条件、种植术式、患者全身因素等,其制定过程需要评估相应临床决策指标及执行不同临床路径。本文回顾了人脑的认知行为及信息处理机制,在临床循证医学的思想及大数据、深度学习的潜力启发下,结合临床决策指标及临床路径可定量或定性分析的数据特点,提出了基于决策指标智能化预测及临床路径智能化执行的种植手术机器人种植决策类脑智能化可行方案,即“挖掘决策指标,厘清临床路径——构建决策指标大数据库——深度学习智能预测决策指标——临床路径智能执行——种植决策类脑智能化”,并结合本团队前期研究成果,以即刻种植时机决策为例,述评其类脑智能化过程,为后续种植决策全面“类脑智能化”研究提供范本。未来,挖掘并评价更多临床决策因素,并不断总结完善种植临床路径,同时采取最佳的智能化方式实现循证指标及路径的智能化预测,最终实现种植临床诊疗过程智能化,将是口腔临床医师们需要思考及努力的方向之一。

At present,implant surgery robots have basically achieved"surgical intelligence",but"brain⁃inspired in⁃telligence"of robots is still in the stage of theory and exploration.The formulation of a clinical implantation plan de⁃pends on the timing of implantation,implantation area,bone condition,surgical procedure,patient factors,etc.,which need to evaluate the corresponding clinical decision indicators and clinical pathways.Inspired by evidence⁃based medi⁃cine and the potential of big data and deep learning,combined with the data characteristics of clinical decision indica⁃tors and clinical pathways that can be quantitatively or qualitatively analyzed,this review simulates the cognitive behav⁃ior and neural mechanisms of the human brain and proposes a feasible brain⁃inspired intelligence scheme by predicting the decision indices and executing clinical pathways intelligently,that is,"select clinical indicators and clarify clinical pathways⁃⁃construct database⁃⁃use deep learning to intelligently predict decision indicators⁃⁃intelligent execution of clinical pathways⁃⁃brain⁃inspired intelligence of implant decision⁃making".Combined with the previous research re⁃sults of our team,this review also describes the process of realization of brain⁃inspired intelligence for immediate im⁃plant timing decisions,providing an example of the comprehensive realization of brain⁃inspired intelligence of implant surgery robots in the future.In the future,how to excavate and summarize other clinical decision factors and select the best way to realize the automatic prediction of evidence⁃based clinical indicators and pathways and finally realize the complete intellectualization of clinical diagnosis and treatment processes will be one of the directions that dental clini⁃cians need to strive for.