Purpose/Significance To systematically review the research progress of deep learning in named entity recognition(NER) in ancient books of traditional Chinese medicine(TCM)，and to provide references for the development of this field. Method/Process By using the literature review method，the core challenges and key technologies of NER in ancient books of TCM are systematically analyzed.The research progress of deep learning in this field is summarized，and prospects are proposed. Result/Conclusion Significant progress has been achieved in research on NER in ancient books of TCM. However，it still faces challenges such as ambiguous entity boundaries， difficulties in term standardization，complex metaphorical expressions，and scarce annotated corpora，etc. Future research should focus on establishing a unified annotation system and high-quality corpora，and developing recognition models that integrate classical Chinese linguistic features with domain knowledge，thereby enhancing the accuracy and generalization capability of NER in ancient books of TCM.