Jinan Municipal Hospital of Traditional Chinese Medicine, Jinan, P.R. China.
Xiyuan Hospital, China Academy of Chinese Medicinal Sciences, Beijing, P.R. China.
J Evid Based Med. 2023 Mar;16(1):91-100. doi: 10.1111/jebm.12517. Epub 2023 Mar 20.
The inheritance of knowledge and experience was crucial to the development of Traditional Chinese Medicine (TCM). However, the existing methods of inheriting the unique clinical experience of famous veteran TCM doctors still followed the outdated and inefficient Master-Prentice schema. In addition, the inherited medical books and records were usually lack of standardization and systematization. In this article, a new method for inheriting the academic thoughts and clinical experience of famous veteran doctors with the help of artificial intelligence technology was explored. Due to the individualized treatment characteristics namely "same disease with different treatments, different diseases with the same treatment," the intelligent inheritance of TCM faced many technical barriers. To tackle these problems, we proposed a prototype system framework for the intelligent inheritance of famous veteran doctors based on rules and deep learning models and performed a case study on the treatment of pediatric asthma. The architecture could not only make full use of the advantages of deep learning, but also integrate the valuable knowledge and experience analysis of famous veteran doctors from injected rules. Specifically, the study took pediatric asthma medical records as training and test samples and calculated the similarity between the generated prescriptions and the real-world clinical prescriptions from the famous veteran doctors. Experimental results showed that the generated prescription could achieve a similarity of more than 90%. It proved that the proposed framework provided a feasible way for the intelligent inheritance and research of the academic thoughts and clinical experience of famous veteran TCM doctors.
知识和经验的传承对中医药的发展至关重要。然而，现有的传承名老中医独特临床经验的方法仍沿袭着陈旧低效的师带徒模式。此外，传承的医籍和记录通常缺乏规范化和系统化。本文探讨了一种借助人工智能技术传承名老中医学术思想和临床经验的新方法。由于中医药个体化治疗的特点“同病异治、异病同治”，中医的智能传承面临着诸多技术障碍。针对这些问题，我们提出了一种基于规则和深度学习模型的名老中医智能传承原型系统框架，并以小儿哮喘的治疗为例进行了案例研究。该架构不仅可以充分利用深度学习的优势，还可以整合来自注入规则的名老中医的宝贵知识和经验分析。具体来说，该研究以小儿哮喘病历作为训练和测试样本，计算生成的处方与名老中医真实临床处方之间的相似度。实验结果表明，生成的处方可以达到 90%以上的相似度。这证明了所提出的框架为名老中医学术思想和临床经验的智能传承和研究提供了一种可行的方法。
