A Novel TCM Prescription Recommendation Method based on Attention Factorization Machines

Authors

  • Wenxuan Xu
  • Qingtao Wu

DOI:

https://doi.org/10.54097/jceim.v10i3.8682

Keywords:

Attention Factorization Machines, Factorization Machines, Prescription Recommendation, Attention Network

Abstract

A prescription recommendation algorithm for attention factorization machines is proposed in this study. This algorithm leverages the pair-wise interaction of factorization machines to capture the multi-category attributes of patients and prescriptions. Additionally, an attention network is incorporated into the factorization machine to assign higher weights to the effective features within the prescription. This enables the algorithm to discern the importance of different combinations of features in the prescription, thereby enhancing the recommendation performance of the model. Through extensive experimentation, it is observed that the prescription recommendation model based on attention factorization machines does not rely on manual features and exhibits commendable recommendation performance. Furthermore, it achieves a certain degree of individualized recommendation effect.

References

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Published

24-05-2023

Issue

Section

Articles

How to Cite

Xu, W., & Wu, Q. (2023). A Novel TCM Prescription Recommendation Method based on Attention Factorization Machines. Journal of Computing and Electronic Information Management, 10(3), 55-61. https://doi.org/10.54097/jceim.v10i3.8682

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