Ma Suya, Liu Jinlei, Li Wenhua, Liu Yongmei, Hui Xiaoshan, Qu Peirong, Jiang Zhilin, Li Jun, Wang Jie
Guang'anmen Hospital, China Academy of Chinese Medicine Sciences, Beijing, 100053, China.
Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Chin Med. 2023 Apr 20;18(1):43. doi: 10.1186/s13020-023-00741-9.
Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summarizing the principles and processes of deep learning and traditional machine learning algorithms, analyzing the application of machine learning in TCM, reviewing the results of previous studies, this study proposed a promising future perspective based on the combination of machine learning, TCM theory, chemical compositions of natural products, and computational simulations based on molecules and chemical compositions. In the first place, machine learning will be utilized in the effective chemical components of natural products to target the pathological molecules of the disease which could achieve the purpose of screening the natural products on the basis of the pathological mechanisms they target. In this approach, computational simulations will be used for processing the data for effective chemical components, generating datasets for analyzing features. In the next step, machine learning will be used to analyze the datasets on the basis of TCM theories such as the superposition of syndrome elements. Finally, interdisciplinary natural product-syndrome research will be established by unifying the results of the two steps outlined above, potentially realizing an intelligent artificial intelligence diagnosis and treatment model based on the effective chemical components of natural products under the guidance of TCM theory. This perspective outlines an innovative application of machine learning in the clinical practice of TCM based on the investigation of chemical molecules under the guidance of TCM theory.
中医已经应用了数千年，具有临床疗效。天然产物及其有效成分，如青蒿素和紫杉醇，在全球范围内挽救了数百万人的生命。人工智能在中医领域的应用越来越广泛。通过总结深度学习和传统机器学习算法的原理及过程，分析机器学习在中医中的应用，回顾以往研究结果，本研究基于机器学习、中医理论、天然产物化学成分以及基于分子和化学成分的计算模拟相结合，提出了一个有前景的未来展望。首先，机器学习将应用于天然产物的有效化学成分，以针对疾病的病理分子，从而能够基于它们所针对的病理机制实现筛选天然产物的目的。在这种方法中，计算模拟将用于处理有效化学成分的数据，生成用于分析特征的数据集。下一步，机器学习将基于中医理论，如证素叠加等，对数据集进行分析。最后，通过整合上述两个步骤的结果，建立跨学科的天然产物 - 证研究，有可能在中医理论指导下，基于天然产物的有效化学成分实现智能人工智能诊疗模型。这一展望勾勒出了在中医理论指导下，基于化学分子研究的机器学习在中医临床实践中的创新应用。
