Published on in Vol 10, No 5 (2022): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35239, first published .
Transformer- and Generative Adversarial Network–Based Inpatient Traditional Chinese Medicine Prescription Recommendation: Development Study

Transformer- and Generative Adversarial Network–Based Inpatient Traditional Chinese Medicine Prescription Recommendation: Development Study

Transformer- and Generative Adversarial Network–Based Inpatient Traditional Chinese Medicine Prescription Recommendation: Development Study

Journals

  1. Ma S, Liu J, Li W, Liu Y, Hui X, Qu P, Jiang Z, Li J, Wang J. Machine learning in TCM with natural products and molecules: current status and future perspectives. Chinese Medicine 2023;18(1) View
  2. Wang Z, Guo Z. Intelligent Chinese Medicine: A New Direction Approach for Integrative Medicine in Diagnosis and Treatment of Cardiovascular Diseases. Chinese Journal of Integrative Medicine 2023;29(7):634 View
  3. Zhao Z, Qian Y, Liu Q, Chen J, Liu Y. A Dynamic Optimization-Based Ensemble Learning Method for Traditional Chinese Medicine Named Entity Recognition. IEEE Access 2023;11:99101 View
  4. Chen Z, Peng P, Wang M, Deng X, Chen R. Bioinformatics-based and multiscale convolutional neural network screening of herbal medicines for improving the prognosis of liver cancer: a novel approach. Frontiers in Medicine 2023;10 View
  5. Li X, Chen K, Yang J, Wang C, Yang T, Luo C, Li N, Liu Z. TLDA: A transfer learning based dual-augmentation strategy for traditional Chinese Medicine syndrome differentiation in rare disease. Computers in Biology and Medicine 2024;169:107808 View
  6. Zeng J, Jia X. Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine. Engineering 2024;40:28 View
  7. Yang Q, Cheng Z, Kang Y, Wang X. A novel multi-view contrastive learning for herb recommendation. Applied Intelligence 2024;54(22):11412 View
  8. Li R, Wu S, Tu J, Peng L, Ma L. An enhanced graph convolutional network with property fusion for acupoint recommendation. Applied Intelligence 2024;54(22):11536 View
  9. Zhao Z, Tang Y, Cheng Z, Leng Y, Tang L. ABL-TCM: An Abductive Framework for Named Entity Recognition in Traditional Chinese Medicine. IEEE Access 2024;12:126232 View
  10. Song Z, Chen G, Chen C. AI empowering traditional Chinese medicine?. Chemical Science 2024;15(41):16844 View
  11. Zhu J, Liu X, Gao P. Digital intelligence technology: new quality productivity for precision traditional Chinese medicine. Frontiers in Pharmacology 2025;16 View
  12. Zeng J, Jia X. Quantifying compatibility mechanisms in traditional Chinese medicine with interpretable graph neural networks. Journal of Pharmaceutical Analysis 2025;15(8):101342 View
  13. Liu Q, Zhang D, Wang B, Zhao W, Zhang T, Sutcharitchan C, Li S. Network pharmacology: Advancing the application of large language models in traditional Chinese medicine research. Science of Traditional Chinese Medicine 2025;3(2):113 View
  14. Wang J, Liu Y, Li J, He H, Liu C, Song Y, Ma S. Artificial Intelligence in Traditional Chinese Medicine: Multimodal Fusion and Machine Learning for Enhanced Diagnosis and Treatment Efficacy. Current Medical Science 2025 View

Conference Proceedings

  1. Kumar C, Sirisati R, Gudditti V, Rao K, Challa R. 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS). A Smart Recommendation System for Medicine using Intelligent NLP Techniques View
  2. Lin Y, Hsu P, Chen R, Sub-r-pa C. Proceedings of the 2024 7th International Conference on Healthcare Service Management. Exploring the Use of Ready-to-Deploy Large Language Models for Opioid Medication Adjustment in Palliative Care Settings View