Application of machine learning methods in research of traditional Chinese medicine
With the rapid development of information technology and the arrival of the digital era,digital technology plays an important role in several Chinese medicine research areas,such as quality control of traditional Chinese medicine(TCM),data mining,discovery of new medicines,optimization of prescription compounding,and clinical diagnosis of Chinese medicine.The application of digital technologies such as machine learning(ML)and deep learning(DL)can optimize the design of TCM research,reduce the time and cost of clinical research,organically combine clinical research with basic research,improve the quality and efficiency of clinical research,and provide a guarantee for the scientificity,objectivity,and standardization of modernized TCM research.Therefore,it is an inevitable trend for the future development of TCM to improve multiple data resources,realize the cross-combined use of multiple digital technologies,and optimize algorithms and models.In recent years,the progress of ML application in the field of TCM research is sorted out,and the analysis illustrates the specific applications of ML methods such as clustering,support vector machine(SVM)and deep learning(DL)in the research of TCM medicinal properties,TCM compounding,TCM toxicity analysis,TCM efficacy research,TCM pharmaceutical process optimization,TCM tablets quality grade classification,mining of TCM clinical medication rules,and analysis of TCM therapeutic principles and pharmacological effect mechanisms.The research aims to explore the application of ML in the study of TCM.It aims to explore the trend of ML application in TCM research and to prospect its application prospect.
machine learningtraditional Chinese medicinealgorithm modelartificial intelligencebig datadeep learning
NETL
NSTL
万方数据
