Artificial Intelligence Meets Chinese Medicine

Intelligent Chinese Medicine: A New Direction Approach for Integrative Medicine in Diagnosis and Treatment of Cardiovascular Diseases

High mortality rates from cardiovascular diseases (CVDs) persist worldwide. Older people are at a higher risk of developing these diseases. Given the current high treatment cost for CVDs, there is a need to prevent CVDs and or develop treatment alternatives. Western and Chinese medicines have been used to treat CVDs. However, several factors, such as inaccurate diagnoses, non-standard prescriptions, and poor adherence behavior, lower the benefits of the treatments by Chinese medicine (CM). Artificial intelligence (AI) is increasingly used in clinical diagnosis and treatment, especially in assessing efficacy of CM in clinical decision support systems, health management, new drug research and development, and drug efficacy evaluation. In this study, we explored the role of AI in CM in the diagnosis and treatment of CVDs, and discussed application of AI in assessing the effect of CM on CVDs.

The intelligent experience inheritance system for Traditional Chinese Medicine

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the existing methods of inheriting the unique clinical experience of famous veteran TCM doctors still followed the outdated and inefficient Master-Prentice schema.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.

Evolution from Medical Imaging to Visualized Medicine

The discovery of X-ray in 1895 and the first X-ray image of Mrs. Röntgen's hand opened up a new era of radiology and the research of medical imaging. The evolution of traditional medical imaging has been lasting for over 100 years, serving the detection, diagnosis, and treatments of human diseases with a clear view of the anatomy information. In late 1990s, the concept of molecular imaging was proposed as the science and technology of molecular biology and bio-engineering rapidly developed, and it directly gave birth to the emergence of precision medicine for clinical lesion-targeted treatments against various cancers and cardiocerebrovascular diseases. Physiological and pathological changes in live bodies from zebrafish to human beings can be imaged to ensure an efficient image-guided therapy. Nowadays, the philosophy of medical and molecular imaging has been a powerful tool and indispensable modality for doctors to make their decisions and give patients reliable advices. With the ever-emerging developments of advanced intelligent technologies such as flexible sensors, medical meta-data analysis, brain sciences, surgical robots, VR/AR, etc., modern medicine has been evolving from traditional medical and molecular imaging to visualized medicine, which has created novel accessible approaches along with cutting-edge techniques for the revolutionized diagnostic and therapeutic paradigms. In this context, the history and milestones from medical imaging to visualized medicine will be elucidated. And in particular, representative visualized medicine advances including its application to COVID-19 epidemics will be discussed in order to look for its important contributions and a future perspective to modern medicine.

Computational Medicine: Past, Present and Future

Computational medicine is an emerging discipline that uses computer models and complex software to simulate the development and treatment of diseases. Advances in computer hardware and software technology, especially the development of algorithms and graphics processing units (GPUs), have led to the broader application of computers in the medical field. Computer vision based on mathematical biological modelling will revolutionize clinical research and diagnosis, and promote the innovative development of Chinese medicine, some biological models have begun to play a practical role in various types of research. This paper introduces the concepts and characteristics of computational medicine and then reviews the developmental history of the field, including Digital Human in Chinese medicine. Additionally, this study introduces research progress in computational medicine around the world, lists some specific clinical applications of computational medicine, discusses the key problems and limitations of the research and the development and application of computational medicine, and ultimately looks forward to the developmental prospects, especially in the field of computational Chinese medicine.

The Impact of Artificial Intelligence on Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) is a well-established medical system with a long history. Currently, artificial intelligence (AI) is rapidly expanding in many fields including TCM. AI will significantly improve the reliability and accuracy of diagnostics, thus increasing the use of effective therapeutic methods for patients. This systematic review provides an updated overview on the major breakthroughs in the field of AI-assisted TCM four diagnostic methods, syndrome differentiation, and treatment. AI-assisted TCM diagnosis is mainly based on digital data collected by modern electronic instruments, which makes TCM diagnosis more quantitative, objective, and standardized. As a result, the diagnosis decisions made by different TCM doctors exhibit more consistency, accuracy, and reliability. Meanwhile, the therapeutic efficacy of TCM can be evaluated objectively. Therefore, AI is promoting TCM from experience to evidence-based medicine, a genuine scientific revolution. Furthermore, huge and non-uniform knowledge on formula-syndrome relationships and the combination rules of herbal TCM formulae could be better standardized with the help of AI analysis, which is necessary for the clinical efficacy evaluation and further optimization on the standardized TCM formulae. AI bridges the gap between TCM and modern science and technology. AI may bring clinical TCM diagnostics closer to western medicine. With the help of AI, more scientific evidence about TCM will be discovered. It can be expected that more unified guidelines for specific TCM syndromes will be issued with the development of AI-assisted TCM therapies in the future.

A Review on Different Kinds of Artificial Intelligence Solutions in TCM Syndrome Differentiation Application

In 1979, the first computer program for TCM diagnosis was launched, although this time was about 30 years after artificial intelligence (AI) came into being and began to be widely used. However, an endless stream of artificial intelligence methods was applied in the field of Chinese medicine research, expert system, artificial neural network, data mining, and multivariate analysis; not limited to what was mentioned, this study tried to make a review on application of AI to TCM syndrome differentiation, while summarizing the artificial intelligence application of TCM syndrome differentiation in the current context. It also provides a theoretical background for the upcoming fully automated research on TCM syndrome differentiation and diagnosis robot.