Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provi...Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provides powerful tools to analyze massive amounts of data, facilitating physicians to make better clinical decisions or even replace human judgment in healthcare.Advanced AI technology also creates novel opportunities for exploring the scientific basis of traditional Chinese medicine(TCM) and developing the standardization and digitization of TCM pulse diagnostic methodology. In the present study, we review and discuss the potential application of AI technology in TCM pulse diagnosis. The major contents include the following aspects:(1) a brief introduction of the general concepts and knowledge of TCM pulse diagnosis or palpation,(2) landmark developments in AI technology and the applications of common AI deep learning algorithms in medical practice,(3) the current progress of AI technology in TCM pulse diagnosis,(4) challenges and perspectives of AI technology in TCM pulse diagnosis. In conclusion, the pairing of TCM with modern AI technology will bring novel insights into understanding the scientific principles underlying TCM pulse diagnosis and creating opportunities for the development of AI deep learning technology for the standardization and digitalization of TCM pulse diagnosis.展开更多
Based on the fuzzy characteristic of the pulse state and syndromes differentiation thinking mode of TCM, an information fusing recognition method of pulse states based on SFNN (Stochastic Fuzzy Neural Network) is pres...Based on the fuzzy characteristic of the pulse state and syndromes differentiation thinking mode of TCM, an information fusing recognition method of pulse states based on SFNN (Stochastic Fuzzy Neural Network) is presented in this paper. With the learning ability in parameters and structure, SFNN fuses the measurement information of three pulse-state sensors distributed in Cun, Guan, and Chi location of body for the pulse state recognition. The experimental results show that the percentage of correct recognition with new method is higher than that by single-data recognition one, with fewer off-line train numbers.展开更多
Pulse diagnosis,an important part of Chinese traditional medicine(TCM),has developed over thousands of years and is still valued and applied worldwide.The process of pulse diagnosis necessitates extensive training and...Pulse diagnosis,an important part of Chinese traditional medicine(TCM),has developed over thousands of years and is still valued and applied worldwide.The process of pulse diagnosis necessitates extensive training and practice by physicians,necessitating the objectification of pulse diagnosis.However,the existing studies on the definition and description of pulse waveforms are incomplete,and the standards for objectification vary,which to some extent affects the further development of pulse diagnosis in TCM.In this research,a concept of pulse matrix is introduced and the definition and description of 13 pulse signals are accomplished through a literature review combined with the characterization methods in time and frequency domains,and a new method of pulse recognition based on Spearman's rank correlation coefficient is introduced.For a single pulse signal,the recognition of the pulse was completed.For continuous pulse signals,a random pulse signal generator was constructed,and the recognition of continuous pulse.Through the recognition experiments of single pulse,continuous pulse and real pulse,the effectiveness and rationality of the method are proved.It provides a promotion for the modern development of TCM pulse diagnosis.With the continuous progress of technology and the deepening of interdisciplinary cooperation,it is believed that TCM will usher in a prosperous development in the near future.展开更多
基金We thank for the funding support form the Health and Medical Research Fund,Hong Kong SAR(No.17181811).
文摘Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provides powerful tools to analyze massive amounts of data, facilitating physicians to make better clinical decisions or even replace human judgment in healthcare.Advanced AI technology also creates novel opportunities for exploring the scientific basis of traditional Chinese medicine(TCM) and developing the standardization and digitization of TCM pulse diagnostic methodology. In the present study, we review and discuss the potential application of AI technology in TCM pulse diagnosis. The major contents include the following aspects:(1) a brief introduction of the general concepts and knowledge of TCM pulse diagnosis or palpation,(2) landmark developments in AI technology and the applications of common AI deep learning algorithms in medical practice,(3) the current progress of AI technology in TCM pulse diagnosis,(4) challenges and perspectives of AI technology in TCM pulse diagnosis. In conclusion, the pairing of TCM with modern AI technology will bring novel insights into understanding the scientific principles underlying TCM pulse diagnosis and creating opportunities for the development of AI deep learning technology for the standardization and digitalization of TCM pulse diagnosis.
文摘Based on the fuzzy characteristic of the pulse state and syndromes differentiation thinking mode of TCM, an information fusing recognition method of pulse states based on SFNN (Stochastic Fuzzy Neural Network) is presented in this paper. With the learning ability in parameters and structure, SFNN fuses the measurement information of three pulse-state sensors distributed in Cun, Guan, and Chi location of body for the pulse state recognition. The experimental results show that the percentage of correct recognition with new method is higher than that by single-data recognition one, with fewer off-line train numbers.
基金the National Natural Science Foundation of China(grant number 12472303,T2288101,U20A20390,11827803)the National Key Research and Development Program of China(grant number 2023YFC3603500)the Fundamental Research Funds for the Central Universities.
文摘Pulse diagnosis,an important part of Chinese traditional medicine(TCM),has developed over thousands of years and is still valued and applied worldwide.The process of pulse diagnosis necessitates extensive training and practice by physicians,necessitating the objectification of pulse diagnosis.However,the existing studies on the definition and description of pulse waveforms are incomplete,and the standards for objectification vary,which to some extent affects the further development of pulse diagnosis in TCM.In this research,a concept of pulse matrix is introduced and the definition and description of 13 pulse signals are accomplished through a literature review combined with the characterization methods in time and frequency domains,and a new method of pulse recognition based on Spearman's rank correlation coefficient is introduced.For a single pulse signal,the recognition of the pulse was completed.For continuous pulse signals,a random pulse signal generator was constructed,and the recognition of continuous pulse.Through the recognition experiments of single pulse,continuous pulse and real pulse,the effectiveness and rationality of the method are proved.It provides a promotion for the modern development of TCM pulse diagnosis.With the continuous progress of technology and the deepening of interdisciplinary cooperation,it is believed that TCM will usher in a prosperous development in the near future.
