卷积神经网络模型在中医辨证论治中的应用现状

Application of convolutional neural network model in TCM treatment based on syndrome differentiation

卷积神经网络模型作为人工智能深度学习技术的代表,因其强大的非线性特征提取能力,在中医辨证论治领域的应用越来越广泛,成为推进中医智能化发展和阐释中医科学理论体系的有效手段。本研究梳理了中医辨证论治各环节与卷积神经网络相关的应用,从中医望诊、针灸腧穴、医案辨证、用药推荐4个方面进行了归纳和总结,并分析了相关技术用于中医辨证论治时存在的问题及发展趋势,可为推动中医与人工智能技术的交叉融合发展提供参考。

Convolutional neural network model,as a representative of AI deep technology,has been applied more and more widely in the field of TCM(Traditional Chinese Medicine)treatment based on syndrome differentiation due to its strong nonlinear feature extraction ability,which has become an effective means to promote the intelligent development of TCM and explain the theoretical system of TCM.In this study,we reviewed the application related to convolutional neural network in each link of TCM treatment based on syndrome differentiation,summarized it from four aspects:TCM inspection,acupuncture and moxibustion and point,medical record syndrome differentiation,medication recommendation,and analyzed the problems and development trends of relevant technologies in TCM treatment based on syndrome differentiation,which could provide reference for promoting the cross-integration development of TCM and AI related technologies.