MR-KPA: medication recommendation by combining knowledge-enhanced pre-training with a deep adversarial network
In: BMC Bioinformatics, Jg. 23 (2022), Heft 1, S. 1-19
Online
academicJournal
Zugriff:
Abstract Background Medication recommendation based on electronic medical record (EMR) is a research hot spot in smart healthcare. For developing computational medication recommendation methods based on EMR, an important challenge is the lack of a large number of longitudinal EMR data with time correlation. Faced with this challenge, this paper proposes a new EMR-based medication recommendation model called MR-KPA, which combines knowledge-enhanced pre-training with the deep adversarial network to improve medication recommendation from both feature representation and the fine-tuning process. Firstly, a knowledge-enhanced pre-training visit model is proposed to realize domain knowledge-based external feature fusion and pre-training-based internal feature mining for improving the feature representation. Secondly, a medication recommendation model based on the deep adversarial network is developed to optimize the fine-tuning process of pre-training visit model and alleviate over-fitting of model caused by the task gap between pre-training and recommendation. Result The experimental results on EMRs from medical and health institutions in Hainan Province, China show that the proposed MR-KPA model can effectively improve the accuracy of medication recommendation on small-scale longitudinal EMR data compared with existing representative methods. Conclusion The advantages of the proposed MR-KPA are mainly attributed to knowledge enhancement based on ontology embedding, the pre-training visit model and adversarial training. Each of these three optimizations is very effective for improving the capability of medication recommendation on small-scale longitudinal EMR data, and the pre-training visit model has the most significant improvement effect. These three optimizations are also complementary, and their integration makes the proposed MR-KPA model achieve the best recommendation effect.
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MR-KPA: medication recommendation by combining knowledge-enhanced pre-training with a deep adversarial network
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Autor/in / Beteiligte Person: | Lin, Shaofu ; Wang, Mengzhen ; Shi, Chengyu ; Xu, Zhe ; Chen, Lihong ; Gao, Qingcai ; Chen, Jianhui |
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Zeitschrift: | BMC Bioinformatics, Jg. 23 (2022), Heft 1, S. 1-19 |
Veröffentlichung: | BMC, 2022 |
Medientyp: | academicJournal |
ISSN: | 1471-2105 (print) |
DOI: | 10.1186/s12859-022-05102-1 |
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