This paper reviews the published articles of recent years on the application of deep learning methods in automatic localization of acupoint

and summarizes it from 3 key links

i.e. the dataset construction

the neural network model design

and the accuracy evaluation of acupoint localization. The significant progress has been obtained in the field of deep learning for acupoint localization

but the scale of acupoint detection needs to be expanded and the precision

the generalization ability

and the real-time performance of the model be advanced. The future research should focus on the support of standardized datasets

and the integration of 3D modeling and multimodal data fusion

so as to increase the accuracy and strengthen the personalization of acupoint localization.