The Impact of Artificial Intelligence on Traditional Chinese Medicine

Wang, Yulin; Shi, Xiuming; Li, Li; Efferth, Thomas; Shang, Dong

doi:10.1142/s0192415x21500622

Cited by 57 publications

(32 citation statements)

References 71 publications

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“…Above all, we define what the "knowledge" in the KG is. For the SYN2 shown in Figure 2, one of the knowledge about SYN2 denoted as Knowl SYN2 can acquire by (2) and the result as (3).…”

Section: Definitions and Task Complexitymentioning

confidence: 99%

“…During clinical diagnosis, doctors integrate TCM theories to identify the syndrome based on patients' symptoms, which are heavily influenced by the doctor's previous experience. AI-assisted TCM diagnosis relies primarily on digital data obtained by modern electronic instruments, making TCM diagnosis more quantitative, objective, and standardized [ 3 ]. Thus, it is necessary to have a computer-aided decision-making model for the diagnosis to balance the uncertainty of human factors.…”

Section: Introductionmentioning

confidence: 99%

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Knowledge-Based Recurrent Neural Network for TCM Cerebral Palsy Diagnosis

Tian

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Cerebral palsy is one of the most prevalent neurological disorders and the most frequent cause of disability. Identifying the syndrome by patients’ symptoms is the key to traditional Chinese medicine (TCM) cerebral palsy treatment. Artificial intelligence (AI) is advancing quickly in several sectors, including TCM. AI will considerably enhance the dependability and precision of diagnoses, expanding effective treatment methods’ usage. Thus, for cerebral palsy, it is necessary to build a decision-making model to aid in the syndrome diagnosis process. While the recurrent neural network (RNN) model has the potential to capture the correlation between symptoms and syndromes from electronic medical records (EMRs), it lacks TCM knowledge. To make the model benefit from both TCM knowledge and EMRs, unlike the ordinary training routine, we begin by constructing a knowledge-based RNN (KBRNN) based on the cerebral palsy knowledge graph for domain knowledge. More specifically, we design an evolution algorithm for extracting knowledge in the cerebral palsy knowledge graph. Then, we embed the knowledge into tensors and inject them into the RNN. In addition, the KBRNN can benefit from the labeled EMRs. We use EMRs to fine-tune the KBRNN, which improves prediction accuracy. Our study shows that knowledge injection can effectively improve the model effect. The KBRNN can achieve 79.31% diagnostic accuracy with only knowledge injection. Moreover, the KBRNN can be further trained by the EMRs. The results show that the accuracy of fully trained KBRNN is 83.12%.

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“…Above all, we define what the "knowledge" in the KG is. For the SYN2 shown in Figure 2, one of the knowledge about SYN2 denoted as Knowl SYN2 can acquire by (2) and the result as (3).…”

Section: Definitions and Task Complexitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Knowledge-Based Recurrent Neural Network for TCM Cerebral Palsy Diagnosis

Tian

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“… 15 – 16 In recent years, several studies have summarized the characteristics of symptoms in TCM and found that diagnosis in TCM can be achieved by bionics instruments. 17 – 19 The application of ICT in the field of medicine and health has become normal, and several TCM doctors have begun using devices as diagnostic tools.…”

Section: Introductionmentioning

confidence: 99%

Perceptions of traditional Chinese medicine doctors about using wearable devices and traditional Chinese medicine diagnostic instruments: A mixed-methodology study

Zhou

Ogihara

et al. 2022

DIGITAL HEALTH

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Objective This study aimed to investigate the perceptions of traditional Chinese medicine doctors about wearable devices and diagnostic instruments and explore the factors that influence them. Methods Data on the perceptions of the traditional Chinese medicine doctors in Hangzhou, China, about wearable devices and diagnostic instruments were collected through face-to-face semi-structured interviews. The author coded the interview responses using grounded theory. A cross-sectional survey was conducted in four traditional Chinese medicine hospitals in Hangzhou, China. The responses of 385 traditional Chinese medicine doctors were considered valid. Descriptive statistics and binary logistic regression models were used for analysis. Results This study categorized the perceptions of traditional Chinese medicine about wearable devices and traditional Chinese medicine diagnostic instruments under convenience, reliability, suitable population, machine usage scenario, and the integration of traditional Chinese medicine and information communication technology. Convenience encompassed portability and the convenience of carrying instruments or wearing the devices and operating them and the human–device interface. Reliability encompassed the underlying principles, accuracy, durability, and reference to diagnosis. Suitability for people encompassed age distinction and disease differentiation. Machine usage scenarios included use in daily life, educational institutions, and primary medical institutions. The combination of traditional Chinese medicine and information communication technology encompassed the integration of traditional Chinese medicine and wearable functions and diagnostic interpretation. The perceptions of traditional Chinese medicine doctors were affected by age, title, type of hospital, and specialty. Conclusions The use of wearable devices and traditional Chinese medicine diagnostic instruments has gradually been accepted by traditional Chinese medicine doctors. Traditional Chinese medicine doctors need to improve their knowledge and skills for information communication technology integration, and their standardized training should incorporate information communication technology and digital health.

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“…TCM has played a crucial role in the treatment of many diseases of Chinese people, such as diabetes, cancer and RA, etc. ( Li et al, 2021a ; Wang et al, 2021b ; Wang et al, 2021d ; Xiang et al, 2021 ). Especially since the outbreak of COVID-19, TCM has played its unique advantages and gradually gained recognition abroad ( Hou et al, 2021 ; Zhao et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

“…With the rapid development of science and technology, AI has attracted much attention in the field of TCM. The application of AI has not only observably improved the reliability and accuracy of diagnosis, but also provides favorable conditions for screening suitable TCM or program for disease treatment, as well as promoting the modernization of traditional medicine ( Wang et al, 2021d ). At present, the establishment of new methods such as systems biology, bioinformatics, integrated pharmacology and network pharmacology has brought new hope for the modernization of TCM research ( Ren et al, 2020 ; Shen et al, 2020 ; Wang et al, 2021c ; Fang et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Practical Implementation of Artificial Intelligence-Based Deep Learning and Cloud Computing on the Application of Traditional Medicine and Western Medicine in the Diagnosis and Treatment of Rheumatoid Arthritis

Wang

Hou

et al. 2021

Front. Pharmacol.

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Rheumatoid arthritis (RA), an autoimmune disease of unknown etiology, is a serious threat to the health of middle-aged and elderly people. Although western medicine, traditional medicine such as traditional Chinese medicine, Tibetan medicine and other ethnic medicine have shown certain advantages in the diagnosis and treatment of RA, there are still some practical shortcomings, such as delayed diagnosis, improper treatment scheme and unclear drug mechanism. At present, the applications of artificial intelligence (AI)-based deep learning and cloud computing has aroused wide attention in the medical and health field, especially in screening potential active ingredients, targets and action pathways of single drugs or prescriptions in traditional medicine and optimizing disease diagnosis and treatment models. Integrated information and analysis of RA patients based on AI and medical big data will unquestionably benefit more RA patients worldwide. In this review, we mainly elaborated the application status and prospect of AI-assisted deep learning and cloud computation-oriented western medicine and traditional medicine on the diagnosis and treatment of RA in different stages. It can be predicted that with the help of AI, more pharmacological mechanisms of effective ethnic drugs against RA will be elucidated and more accurate solutions will be provided for the treatment and diagnosis of RA in the future.

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The Impact of Artificial Intelligence on Traditional Chinese Medicine

Cited by 57 publications

References 71 publications

Knowledge-Based Recurrent Neural Network for TCM Cerebral Palsy Diagnosis

Knowledge-Based Recurrent Neural Network for TCM Cerebral Palsy Diagnosis

Perceptions of traditional Chinese medicine doctors about using wearable devices and traditional Chinese medicine diagnostic instruments: A mixed-methodology study

Practical Implementation of Artificial Intelligence-Based Deep Learning and Cloud Computing on the Application of Traditional Medicine and Western Medicine in the Diagnosis and Treatment of Rheumatoid Arthritis

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