Hui-Yong HUANGa, Jun-Feng YANa, Zhi-Xi HUa
a.Hunan University of Chinese Medicine, Changsha, China, 410208
Digital Chinese medicine is an emerging interdisciplinary field developed from Traditional Chinese Medicine and information science. In this article, weconsider the significance andpropose an architecture for digital Chinese medicine research, and highlight the key tasks that need to be performedto provide references for the integration of information science into Chinese medicine research.
Traditional Chinese medicine (TCM) is a medical science that has been practiced for thousands of years, involving the study of human physiology and pathology, disease diagnosis, prevention, and treatment, as well as healthcare and rehabilitation. The Chinese National Committee for Terms in Science and Technologies defined TCM as follows: "with Chinese medicine theory and practical experience as its main body, it is a comprehensive science that studies the law of transition between health and disease in human activities, combining prevention, diagnosis, treatment, rehabilitation and healthcare". TCM is widely valued in China, and forms the basis of Kampo medicine in Japanese, Koryo medicine in North Korea, and traditional medicine in South Korea and Vietnam. The efficacy of TCM has been repeatedly demonstrated in medical practice, and its holistic concept of disease prevention and treatment, based on syndrome differentiation, preventative treatment, and other ideas has attracted increasing attention in current medical research and development. However, it is necessary to identify ways of promoting the modernization of TCM research and adapting this research to meet international requirements. The strategic modernization of TCM requires its digitalization, normalization, and standardization. The rapid development of information science, including artificial intelligence, cloud computing, big data, and the internet of things, involving networks of electronic devices, provides strong technical support for modernizing TCM research, effectively addressing the problems of knowledge transfer, resource utilization, promotion, and application, as well as offering a service model that could meet the requirements of modern societies. Digital TCM research, in particular, the establishment of a digital TCM research system, will provide the foundation for exploring new models and methods to achieve the transfer of information and development of TCM. Digitalization supported by information science and technology thus offers new opportunities for the modernization of TCM.
2.The significance of digital TCM research
1) Digital TCM is an emerging interdisciplinary field developed from TCM and information science. It involves the digital reproduction of the ideological theories, thinking, and practical experiences of TCM in studying the complex system of the human body. The establishment of this new digital TCM system focuses on the need to develop several factors, including ① basic TCM theories, which currently lag behind the clinical application of TCM ② an objective service-evaluation system for the disease prevention, treatment characteristics, and benefits of TCM, to meet the needs of its promotion and utilization in society, and ③ the normalization and standardization of digital TCM-related technological achievements, to meet the requirement of the international market. The aim of digital TCM research is therefore to improve understanding of the scientific connotations of TCM theory, enhance the scientific aspects of TCM research, analyze and evaluate clinical diagnosis and treatment reports of TCM, and continue to improve and enhance the health service capabilities of TCM, thus creating a new system digital TCM to meet the specific needs of the current research in the field.
2) Innovative academic research methods for TCM. TCM research has tended to involve passing on information based on personal experiences and learning, together with study of the literature BUT less focus on data analysis and experimental evidence. However, around the middle of last century, it was proposed that TCM and Western medicine should be treated equally, with an emphasis on their combination. New technologies and achievements have been integrated into TCM research, with important results in experimental pharmacological studies, including the extraction of medicinal compounds in the Chinese Materia medical. You-You TU's Nobel Prize-winning work represents a milestone in TCM scientific research, opening up a new era of experimental research that is now receiving increasing attention. However, the preservation and transmission of TCM's culture and achievements and its innovative and sustainable modernization remain important issues. Artificial intelligence, cloud computing, big data, and the internet of things offer a new vision and new opportunities for TCM research and for the development of innovative ideas and academic achievements.
From the 1970s, Wen-Feng ZHU focused on digital methods relating to TCM syndrome differentiation and developed China’s first digital TCM syndrome-differentiation system involving ‘differentiation of syndrome elements’[4,5,6]. Zhen-Qiu GUO also proposed the idea of microcosmic syndrome differentiation based on experimental research into the material basis of TCM syndromes. Targeting the dilemma that clinical TCM practice fails to meet modern needs, Bao-Yan LIU proposed to accelerate its development using digital techniques.With the aim of creating a digital technology for differentiating syndrome elements, Jun-Feng YAN approached the problem from multiple perspectives and subsequently laid the foundations for a method of differentiating syndrome elements[9,10,11,12]. Numerous other scholars have investigated digital models in relation to basic TCM research, developing diagnostic methods, and evaluating the efficacy of Chinese Materia medical, and have proposed the concept of digital TCM anthroposomatology.
Modern scientific and technological methods and processes should be used to promote the modernization of TCM and to verify its scientific theories. Through adopting modern metrology, digitalization, and standardization practices, digital TCM can maintain the traditional system whilst promoting new academic innovations .
3) Promote precision in the advancement of TCM. The advantages of TCM include its ambiguous and macroscopic approach under a holistic concept, while its disadvantages include a lack of accurate understanding of the disease and human body at the local and microscopic levels. However, developments in various omics such as metabonomics, genomics and proteomics, combined with information science and technologies such as system modeling and simulation, big data analysis, and deep learning, can aid the quantification of a TCM syndrome-detection index, and the digitalization and objectification of its efficacy-evaluation system, thus helping promote holistic TCM treatments whilst enhancing their accuracy and precision.
4) Improving the health service capacity of TCM. The accumulation of ancient medical texts and modern medical and biological research literature, together with constantly updated multimedia information and other TCM-related data and resources, has generated ‘big data’. Furthermore, the application of wearable devices and the introduction of the mobile medical era is expected to lead to exponential increases in the amounts of personalized diagnostic and treatment data. It is, therefore, necessary to continue to update data-mining and analytical methods and to improve research ideas and methods to utilize these data for research. Widely used information science and technologies, such as digital information and network communication technologies and the internet of things, allow the collection, storage, analysis, and use of massive amounts of data, greatly improving data extraction and integration capacities and enabling the analysis and mining of otherwise hidden data. Driven by clinical problems and guided by the available data, a data model will allow a new chart of contemporary Chinese medicine to be created, which will stimulate innovative achievements based on thousands of years of rich practical experience, and enhance personalized diagnosis and treatment based on improved syndrome differentiation, prediction of health conditions, disease prevention and treatment, and services for health promotion.
3.Architecture of digital Chinese medicine research
Current rapid developments in new-generation information science and technologies, such as artificial intelligence, cloud computing, big data, the internet of things and mobile internet, provide new ideas and technical support for the development of digital TCM. We discuss the architecture of a digital TCM research system from four aspects, including epistemological, theoretical, technical, and application approaches, based on Xue-Sen QIAN’s hierarchical thinking on modern science and technology systems.
Every discipline or research field has its guiding ideology and epistemology. Digital TCM uses systematic scientific big data, and computational thinking as its basic approaches for understanding and analyzing the complex human body.
The human body is a complex open system. Not only are the organs, meridians, collaterals, and orifices physiologically and pathologically associated, but the human body also has complex, non-linear, and diverse interactions with the environment and society. The theory of TCM emphasizes the idea that the physiological and pathological evolution of the body as a whole is consistent with the systematic integrity and complexity emphasized in systems theory. Using complex systematic thinking to express life phenomena and processes thus has fundamental effects on research and thinking in relation to TCM.
TCM emphasizes experience, integrity, and practice, but the resulting data lack precision and standardization, and the emphasis is thus on an integrated but more general level. Big data thinking highlights the ability to handle diverse data from many sources, and in different modes and formats. Causal relationships are less of a priority in the era of big data, with more emphasis laid on correlations. Big data thinking encourages the analysis of correlations among large data sets, compared to looking for causal relationships in small, more precise samples, as promoted by small data thinking. Mining and analysis of large samples of TCM data will thus allow the detection of correlations that will, in turn, provide a scientific expression for TCM.Computational thinking is one of the three major scientific thinking contexts, with a focus on abstraction and automation. These approaches, together with the application of computer technologies and tools, can help define system boundaries and model systems, simulate and analyze systemic ideas and views, and allow big data-related analysis based on holistic and correlative thinking. Computer science and technology have been widely used in the field of TCM, and also form the cornerstone of TCM digitalization. When dealing with a large and complex information system such as the human body, computational methods are needed to express, abstract, decompose, examine, and predict the clinical problems of TCM. Digital TCM research thus needs to adopt not only complex systemic scientific and big data approaches, but also computational methodological guidance.
This stage addresses the digitization of basic TCM theory. Taking computing as its core, it utilizes a computational approach with abstraction, automation, design, communication, collaboration, memory, and evaluation as basic concepts to realize the formalization, programming, and automation of basic TCM theory, including three aspects:
1) Knowledge expression in TCM. Based on the theories behind basic TCM, systemic scientific theory, and scientific thinking, we can examine the rules for expressing TCM terms and the formal representation of semantic relations, the thinking mechanisms, the TCM model of syndrome differentiation and its digital form, to construct a human-like cognitive architecture based on a unified theory of TCM syndrome differentiation.
2) Information expression in TCM. The classification of TCM information can be considered from the aspects of information classification, representation, and standardization. The ways of expressing TCM information can be examined in ancient medical texts, modern literature, multimedia clinical data, and by real-time dynamic data collection. The standards and norms of TCM data elements, clinical practices, and herbal medicines, as well as the standards and norms for information management in teaching, scientific research, and clinical practice, can all be studied.
3) Computational expression in TCM. Computational approaches can be used to simulate the concepts, principles, and mechanisms of basic TCM theories, and thus to build various mathematical, computing, and learning models for applications in teaching, scientific research, and clinical practice.
At this level, digital technology can use digitized data from various TCM disciplines, including syndrome differentiation, to construct a theoretical digital model focusing on various stages of syndrome differentiation and treatment, along the clinical lines of ‘disease-syndrome-method-formula’. This includes three aspects:
1) Techniques and tools for acquiring life status information. This involves the study of technologies for the rapid acquisition, storage, and processing of big data related to TCM. It also identifies techniques and tools for carrying out diagnoses, digitizing TCM literature, creating electronic medical records related to TCM, and mapping existing TCM-related big data knowledge. This involves the development of signal acquisition instruments and software for system integration, and the secondary development of equipment based on four TCM diagnostic methods, as well as various kinds of portable electronic medical instruments.
2) Techniques and tools for digital syndrome differentiation. Based on the theoretical syndrome-differentiation model, big data analysis and processing technology can be utilized to study the characteristics of and relationships among various TCM syndrome-differentiation systems, to construct scales and dynamic models of diagnostic thresholds for elements in syndrome-differentiation systems, and develop new methods, techniques, and tools to integrate aspects of various syndrome-differentiation systems and thus improve clinical diagnosis and treatment.
3) Techniques and tools for comprehensive evaluation of human life status. Artificial intelligence and big data technology can be used to study the relationships among diseases, syndromes and symptoms, syndromes and medications, and TCM syndrome-differentiation decision-making methods and reasoning engine technology in order to develop intelligent diagnostic tools and TCM knowledge-management tools. This approach will promote big data analysis and processing technology, establish a mining framework suitable for the complex characteristics of TCM data, and research and develop big data mining-analysis tools for the TCM industry.
This stage utilizes clinical digitalization of TCM to create a technical support system for the collection, management, and utilization of TCM-related clinical data, by applying various digital technologies and tools developed at the technical level (above), to carry out integrative research covering clinical practice, scientific research, and information management, with reference to TCM syndromes, core formulae, and effective treatment programs. This stage includes the following aspects:
1) Analysis and management of clinical TCM information. Based on TCM big data, especially the mass of clinical data from TCM hospitals, big data technology can be used to study data cleaning, identify clinical features, and for clinical data analysis and mining. Focusing on the management of TCM hospitals and electronic medical records, this approach will allow us to study the integration, management, and application of information systems in TCM hospitals, as well as the TCM clinical data storage and management technologies.
2) Discovery of clinical TCM knowledge. Research into modern methods of passing on traditional TCM knowledge uses various approaches, including sorting of TCM literature, TCM knowledge-management tools, and experience of renowned and experienced TCM experts. The establishment of ancient and modern TCM literature databases, and a database containing information and clinical experiences of experts, and a TCM ontology knowledge database would allow the establishment of an open platform for sorting literature and information resources relating to TCM.
3) Decision support for TCM auxiliary diagnosis and treatment. Technology can be used in areas such as research into clinical diagnosis decision-making, the use of decision-making formulae, and epidemic prediction. A TCM big data repository, ontology knowledge mapping, and a spatio-temporal evolution model can be used to create a fusion-model decision-recommendation algorithm to aid TCM-related clinical diagnosis and decision-making.
4) Clinical efficacy and safety evaluation of TCM. A clinical follow-up system and feedback system for efficacy evaluation can be established to investigate the efficacy and safety of TCM. Big data analysis can be used to evaluate the efficacy of specific interventions, thus establishing an efficacy-oriented syndrome-differentiation system, in which syndrome, treatment, and efficacy are closely associated. Research would aim to develop a data-sharing mechanism for TCM-related information with appropriate privacy-protection mechanisms to provide effective resistance against cyber-attacks.
5) Intelligent service platform for digital TCM resources. We aim to build a platform for collaborative cooperation, telemedicine, public information services, emergency response, and prevention and control of major diseases in relation to TCM, and to form a cloud-based platform for public services and universal medical services. The system architecture and technologies of public service platforms for TCM can be studied in relation to cloud computing and the internet of things, with the construction of a scientific-data-integration platform to carry out high-performance computing of TCM-related data. A TCM-related hospital information service network and digital TCM clinic service platform can be developed to provide a smart information-notification and knowledge-inquiry system, and to set up a scene-based communication channel between doctors and patients, providing preventive healthcare, health assessments, medical counseling, and other public services in TCM.
4.Current key tasks in digital TCM research
An integrative approach to TCM clinical practice and scientific research requires four approaches. The key tasks in each of these approaches are explained below:
1) Basic research in digitization technology. Research into key technologies and approaches to TCM in terms of clinical information collection, clinical decision-making, and evaluation of curative effects is needed to make better use of modern information technology in scientific research and clinical services for TCM. This requires the construction of a standard TCM information system, integration and management of an information system in TCM hospitals, methods for clinical data collection, analysis, and mining, intelligence-aided TCM clinical decision-making, knowledge management, and medical information-related teaching courses. The current key tasks include researching the expression of TCM knowledge and a standard TCM information system, to lay the foundations for establishing a technical support system for the exchange of TCM-related information.
2) Digitalization and application of TCM diagnostic methods. Current TCM diagnostic approaches are subjective, abstract, vague, and uncertain. Digital technology could thus be used to help collect comprehensive disease information and hence improve diagnostic accuracy, as well as constructing an objective, standardized, and measured diagnosis and treatment system as the core of digital TCM research. This approach entails the standardization and quantification of TCM-based methods of syndrome differentiation, the establishment of a network model of TCM syndromes, the objectification and standardization of TCM-based diagnostic and therapeutic instruments, and the digitization of TCM diagnostic teaching. The current key tasks are to investigate information-acquisition technologies and develop intelligent tools for the Four Diagnostic methods, based on standard TCM information, and to improve the accuracy and practicality, and promote the objectification, normalization, and standardization of the Four Diagnostic methods through a combination of scientific research, and using industrial and clinical diagnostic instruments.
3) Digitalization and application of standard TCM formulae. This approach aims to provide scientific standards and resource management for the production and clinical application of TCM materials, decoctions, and preparations, and to conduct digital research into TCM formulae. This involves research into the standardization of TCM production and quality control technologies, the construction of a database of formulae, and digital research into TCM formulae. The main task involves establishing a quality standard system and technical production standards for the raw materials, intermediates, and finished products.
4) Digitalization and application of TCM in clinical practice. The aim is to carry out systematic studies of the standardization of clinical diagnosis, diagnosis and treatment schemes, and efficacy evaluation systems in TCM in order to construct a technical support system for the collection, management, and utilization of related clinical data. This will entail the standardization of TCM-related clinical diagnoses and treatments, the integration of current and historical TCM information and clinical research, the creation of an information service network of TCM hospitals and a service platform for TCM clinics, demonstration research and demonstration application of digital TCM hospital. Notably, the key task currently involves carrying out studies related to efficacy evaluation standards in TCM, through the standardization and normalization of clinical terms and a clinical evaluation system that can repeatability differentiate among TCM clinical syndromes, thus improving diagnostic and therapeutic accuracies.
Research into digital TCM represents a huge and complex systemic project that is crucial for modernizing TCM research. The construction of an effective and scientific organization and management system, an interdisciplinary training model combining researching with teaching, and a collaborative operational model integrating interdisciplinary talents, technologies, and platforms will vigorously promote digital TCM research. The establishment of a new digital TCM system will also lay the foundations for the subsequent establishment of intelligent digital TCM disciplines.
The authors declare no conflict of interest.
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