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Study on Constructing an Intelligent Prescription Model for LI Suqing＇s Treatment of Recurrent Respiratory Tract Infections Based on Pre-training Transfer Learning
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Changyong LUO1, Zhi LIU2, He YU3, Yurou YAN4, Junhong WANG4, Bing HE4, Xiaohong GU3
Chinese Archives of Traditional Chinese Medicine | 2025, 43(4) : 14 - 17
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Chinese Archives of Traditional Chinese Medicine | 2025, 43(4): 14-17
• Digital Traditional Chinese Medicine •
Study on Constructing an Intelligent Prescription Model for LI Suqing＇s Treatment of Recurrent Respiratory Tract Infections Based on Pre-training Transfer Learning
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Changyong LUO1, Zhi LIU2, He YU3, Yurou YAN4, Junhong WANG4, Bing HE4, Xiaohong GU3
Affiliations
  • 1.Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, China
  • 2.Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu, China
  • 3.Beijing University of Chinese Medicine, Beijing 100029, China
  • 4.Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China
Published: 2025-04-10 doi: 10.13193/j.issn.1673-7717.2025.04.003
Outline
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Objective

This study aimed to construct a deep learning model for the treatment of recurrent respiratory tract infections by using pre-training transfer learning methods.

Method

Firstly，a large number of medical case data from Professor LI Suqing’s tutor was used as the source domain knowledge data. Based on the Sequence to Sequence（seq2seq）Algorithm of Long Short-Term Memory Network（LSTM），It combined the two attention mechanisms of symptom and drug attention to pre-train the model. Then，Professor LI Suqing＇s typical medical cases were used as target domain knowledge data for transfer learning training.

Result

The Turing Test results showed that the error rate of participating traditional Chinese medicine doctors exceeded 30%，with the lowest error rate among those who had long-term follow-ups with Professor LI Suqing. Further qualitative and quantitative evaluation showed that the average score of the model using transfer learning method was 6.14，which was very close to the score of Professor LI Suqing＇s original prescription model of 6.50，while the score of the simple LSTM model was lower.

Conclusion

Pre-training transfer learning method performed well in simulating the prescription patterns of famous traditional Chinese medicine doctors，providing an effective solution for the artificial intelligence-assisted decision-making system of traditional Chinese medicine，and demonstrating the great potential of deep learning in the field of traditional Chinese medicine.

inheritance of famous doctors  /  transfer learning  /  LI Suqing
骆长永, 刘智, 于河, 闫雨柔, 王俊宏, 何冰, 谷晓红. 基于迁移学习构建李素卿治疗反复呼吸道感染智能处方模型. 中华中医药学刊, 2025 , 43 (4) : 14 -17 . DOI: 10.13193/j.issn.1673-7717.2025.04.003
Changyong LUO, Zhi LIU, He YU, Yurou YAN, Junhong WANG, Bing HE, Xiaohong GU. Study on Constructing an Intelligent Prescription Model for LI Suqing＇s Treatment of Recurrent Respiratory Tract Infections Based on Pre-training Transfer Learning[J]. Chinese Archives of Traditional Chinese Medicine, 2025 , 43 (4) : 14 -17 . DOI: 10.13193/j.issn.1673-7717.2025.04.003
Appendix
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Year 2025 volume 43 Issue 4
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Article Info
doi: 10.13193/j.issn.1673-7717.2025.04.003
  • Online Date：2026-10-30
  • Published：2025-04-10
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Affiliations
    1.Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, China
    2.Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu, China
    3.Beijing University of Chinese Medicine, Beijing 100029, China
    4.Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China
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https://castjournals.cast.org.cn/joweb/zhzyyxk/EN/10.13193/j.issn.1673-7717.2025.04.003
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表12种不同金属材料的力学参数
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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