Incorporating Artificial Intelligence and Traditional Chinese Medicine (TCM) into a Western Medical Practice: A Case Study Volume 56- Issue 3

Robert W McGee*

• Fayetteville State University, USA

Received: April 23, 2024; Published: May 07, 2024

*Corresponding author: Robert W McGee, Fayetteville State University, USA

DOI: 10.26717/BJSTR.2024.56.008864

Abstract PDF

The goal of this study was to provide some guidance on how western medical practitioners can incorporate artificial intelligence (AI) and traditional Chinese medicine (TCM) into their medical practice. Artificial intelligence has become an increasingly popular adjunct to medical practices in recent years and will probably be used even more frequently in the years to come. It has an increasingly large number of applications to a wide range of medical specialties and can make medical practices more efficient in operation and can also aid in medical research. Two chatbots, Microsoft Copilot and Elicit were used to demonstrate how AI can be used in medical research. The first step was to find relevant research studies. The second step was to use AI to summarize one of the research studies that had been published in a medical journal. The topic to be researched was dawu (a.k.a. Da Wu), a set of qigong exercises, to see what kind of studies had been made of this tool of traditional Chinese Medicine (TCM). One relevant study was found. The PubMed database was then utilized to find the article and Elicit was used to summarize the study’s findings. Elicit did a decent job of summarizing the study’s findings, but the depth and detail were not adequate to satisfy the researcher, who then decided to read the entire article in order to write up a more complete summary. The conclusion was that artificial intelligence can be utilized as a tool of medical research, but it should only be the starting point of such research. It can be used as a way to find and summarize relevant research, but AI has not yet developed sufficiently to go farther. Human brains still must be used to carry the research beyond the initial stages.

Keywords: Dawu; Tai Chi; Qigong; Traditional Chinese Medicine; TCM; Artificial Intelligence; Elicit; Copilot

The goal of this study is to provide some guidance on how western medical practitioners can incorporate artificial intelligence (AI) and traditional Chinese medicine (TCM) into their medical practice. Artificial intelligence has become an increasingly popular adjunct to medical practices in recent years and will probably be used even more frequently in the years to come [1-27]. It has an increasingly large number of applications to a wide range of medical specialties and can make medical practices more efficient in operation. Traditional Chinese medicine has been used for centuries to treat or cure a wide range of ailments [28-54]. Its focus has been on prevention rather than treatment, but it has also been used to treat existing ailments. TCM has several branches, the most important of which are acupuncture, acupressure, herbal concoctions, tai chi and qigong exercises. Due to space limitations, we shall confine our discussion to tai chi and qigong applications. AI can be used to quickly find basic information on many medical topics, although care must be taken when reading the results of an AI-generated search, since prior studies have found that results have not always been accurate [55].

The quality of AI search findings will undoubtedly improve over time, but we are not yet at the stage where we can totally trust their results. AI-generated searches can be used as a starting point for information retrieval but should not be the final step in any research project. AI chatbots can be used to generate summary information on particular topics. To show how chatbots can be used in this manner, I have decided to use Microsoft Copilot [56], one of the better chatbots as of this writing. Using a chatbot to do the preliminary work saves much time because practitioners who are not familiar with the topicqigong and tai chi in this case -- can be spared the time and trouble of reading hundreds or thousands of pages of explanatory literature on the topic [57-69]. The way to generate information is to give the chatbot a command or instruction. The instruction in this case might be: “Give a brief summary of tai chi and qigong. What are their common features and what are their differences?”

Certainly! Let’s delve into the fascinating world of Tai Chi and Qigong, two ancient Chinese practices that share common roots but also exhibit distinct characteristics. Here’s a concise exploration of their key features and differences:
1. Historical Background and Evolution
o Tai Chi
• Developed in the 16th century by Chen Wangting, a retired warrior, Tai Chi (or Tai Chi Chuan) initially served as a martial art form.
• Over time, it evolved, drawing influences from Taoist and Confucian philosophies. It transformed into a practice that includes self-defense techniques, meditation, and a harmonious balance between mind and body.
• Different styles of Tai Chi, such as Yang, Wu, and Sun, emerged, each with unique characteristics while retaining core principles of fluidity, control, and relaxation.
o Qigong
• Qigong’s history dates back over 5,000 years, making it one of the oldest forms of health care globally.
• Rooted deeply in traditional Chinese medicine, philosophy, and martial arts, Qigong was initially practiced for spiritual growth and longevity.
• It emphasizes breathing techniques, gentle movements, and meditation. Over time, various forms of Qigong have evolved, each serving different health and spiritual purposes.
2. Movement Style and Practice
o Tai Chi
• Characterized by a series of flowing, interconnected movements or forms.
• Examples include the Yang style, known for its gentle, wide-ranging motions, and the Chen style, which incorporates more explosive movements and greater physicality.
• Each Tai Chi movement, such as “Wave Hands Like Clouds” or “Grasp the Sparrow’s Tail,” has a specific posture and sequence, often carrying symbolic meanings.
• Practicing Tai Chi feels like a slow, meditative dance, demanding precision and fluidity.
o Qigong
• Involves simpler, repetitive movements or static postures that are easier to learn and execute.
• Examples include “Lifting the Sky,” a movement for stimulating energy flow, and “Standing Like a Tree,” a meditative posture for grounding and centering.
3. Purpose and Emphasis
o Tai Chi
• Originating as a martial art, Tai Chi emphasizes self-defense, coordination, and balance.
• It requires significant time and dedication to master due to its complexity.
o Qigong
• Rooted in spiritual and healing practices, Qigong provides a more accessible and varied approach.
• It focuses on internal healing, stress relief, and energy cultivation.
• Qigong is suitable for those seeking longevity, health, and maximum human potential.
In summary, while Tai Chi offers a structured approach to bodymind integration, Qigong provides a more accessible path, emphasizing internal healing and energy flow. Both practices contribute to overall well-being, catering to diverse personal needs and preferences.

In the present author’s opinion, these summaries are good enough for a medical practitioner who is unfamiliar with these exercise sets to obtain a basic understanding of the similarities and differences between these two tools of Chinese medicine practitioners. Both tai chi and qigong awaken and energize the body’s natural healing power, which then flows to the affected area. Western medical practitioners who would like to incorporate one or more of these exercise sets into a practice would be wise to seek out the services of a tai chi or qigong practitioner who has several years of experience practicing and using some of these sets. One way to find such practitioners would be to contact a kung fu or tai chi school in the local area. The people in these schools can probably put you in touch with one or more practitioners.

Baduanjin is the most frequently used set of qigong exercises used in medical research [30,42,54] but it is not the only one. The Chinese Health Qigong Association has instruction manuals on several other sets of medical qigong exercises [70-77]. I decided to search the PubMed database [78] to see if some of these other exercise sets had been used in medical research. My first search term was “Da Wu,” one of the other sets of qigong exercises suggested by the Chinese Health Qigong Association. My search using that key word turned up empty. No medical studies could be found that included this key word in either the title or abstract. The Chinese often combine several words when the Chinese characters are translated into English, so I decided to do a search using the key word “dawu.” This time I was able to find one study that used Da Wu, as well as some other qigong exercise sets. It was a comparative study that evaluated the results of several different sets of qigong exercise sets, of which Da Wu was one, and compared those results to those of a no exercise group and an aerobic exercise group [79]. I next went to Elicit AI [80], another artificial intelligence bot, to see if I could find additional studies. I gave it the following command: “Find medical studies that incorporated the use of dawu, also called da wu, a set of qigong exercises, to treat or cure a disease or ailment.”

It gave me a summary and citation for eight studies on the health benefits of qigong, none of which included dawu in the title or abstract [81-88]. This search exercise provided a good example of how chatbots can give imperfect or irrelevant information. In this case, the information was not totally irrelevant because it gave good summaries of qigong studies other than dawu. A close look at the references shows that the chatbot sometimes gave incomplete references that did not follow acceptable APA or other format. I decided not to correct these flaws so that the reader could see what the actual references looked like that were generated by the chatbot.

At this point I decided to use the “Extract data from PDFs” feature of Elicit. This feature provides a summary of the contents of PDF documents, which can be a big time-saver for researchers. I uploaded the Gao, et al. [79] article [81], since that was the only article I could find that was on point. Elicit gave me the following summary: “The summary is that the study systematically reviewed the effects of different traditional Chinese exercises on blood lipids in middle-aged and elderly individuals, highlighting the potential of WQX as the best TCE treatment for dyslipidemia, emphasizing the importance of managing lipid profiles in this population.” The problem with this summary is that the reader is not told what the abbreviations stand for, making it necessary to read the paper to obtain this information. However, the summary did provide some useful information.

I then asked it to give me the main findings. This is what it gave me: “WQX and TJQ were found to be effective in improving blood lipid indicators, with WQX being ranked as the best intervention, followed by BDJ.” Again, Elicit did not disclose what the abbreviations stood for, making it necessary to read the paper. However, a summary of the main findings was not without value. It did disclose the fact that some exercises were effective, and that some exercises were more effective than others.

I next clicked on the link for Methodology. This I what Elicit gave me. “The methodology involved searching Chinese and English databases, creating a search strategy using MeSH terms, keywords, and phrases, defining inclusion and exclusion criteria based on PICOS, and having two researchers independently review and evaluate the selected articles.” Elicit provided many other summary links as well, including:

• Intervention
• Outcome measured
• Limitations
• Intervention effects
• Summary of introduction
• Summary of discussion
• Study design
• Study objectives
• Theoretical framework
• Research question
• Research gaps
• Hypotheses tested
• Future research
• Funding source
• Dataset
• Study count
• Independent variables
• Dependent variables
• Measured variables
• Region
• Duration
• Statistical techniques
• Experimental techniques
• Algorithms
• Software used
• Participant count
• Population characteristics
• Participant age
• Population sex
• Organism
• Policy recommendations

Because I determined that the summary provided by Elicit did not give the details or the depth that I had hoped for, I decided to actually read the paper so that I would be able to write my own summary, which is as follows:

• Gao, et al. [81] examined the effect of six traditional Chinese exercises on blood lipids on middle-aged and elderly patients. The exercises included in the study were tai chi (taijiquan), wuqinxi, baduanjin, liuzijue, yijinjing and dawu. The results were measured against a no exercise group and an aerobic exercise group. The results were as follows:
• For HDL-C, liuzijue, baduanjin, taijiquan and wuqinxi were superior to the no exercise group (p < 0.05). Differences in mean scores for the other two Chinese exercises compared to the no exercise group were not significant.
• For LDL-C, almost all Chinese exercises showed statistical differences in reducing LDL-C levels compared to the no exercise and aerobic exercise groups.
• All six Chinese exercises were effective in improving blood lipid indicators.
• Wuqinxi and taijiquan “can be effective for all four blood lipid indicators and seem to be recommended as the most appropriate way for the elderly to exercise.”
• The rankings indicated that wuqinxi was the most effective in improving blood lipids.

The main finding of the present study is that Elicit, an artificial intelligence bot, can be used as a good starting point for further medical research. Not only was it able to provide a decent short summary of findings for a long and technical article, but it was also able to focus on a wide range of subaspects of the study, making it easier for medical researchers to determine the contents and value of a study without first having to read the entire study. However, I had to read the study in order to obtain the level of depth and detail that I wanted because the summary provided by Elicit was inadequate for my needs. Elicit can be used as a screening process, a first step, that can save time and effort for medical researchers. Upon reading the summary, I was able to determine that the article was worth reading in its entirely.

1. M Ablameyko, N Shakel (2022) Doctor-Patient-Artificial Intelligence Relations in Smart Healthcare. Biomed J Sci & Tech Res 44(5).
2. Marcos AM Almeida, Matheus HC de Araujo (2023) The Use of Artificial Intelligence in the Classification of Medical Images of Brain Tumors. Biomed J Sci & Tech Res 53(4).
3. Emmanuel Andrès, Nathalie Jeandidier, Noel Lorenzo Villalba, Laurent Meyer, Abrar Ahmad Zulfiqar (2020) Currents and Emerging Technologies for Diabetes Care. Biomed J Sci & Tech Res 25(2).
4. Archana P, Lala Behari S, Debabrata P, Vinita S (2019) Artificial Intelligence and Virtual Environment for Microalgal Source for Production of Nutraceuticals. Biomed J Sci & Tech Res 13(5).
5. Ahmed Asfari (2021) Artificial Intelligence Role and Clinical Decision Support System Extubation Readiness Trail and Etiometry Scoring System. Biomed J Sci & Tech Res 35(1).
6. Ashis Kumar D, Harihar Bhattarai, Saji Saraswathy Gopalan (2019) Determinants of Generic Drug Use Among Medicare Beneficiaries: Predictive Modelling Analysis Using Artificial Intelligence. Biomed J Sci & Tech Res 22(1).
7. Chris Caulkins (2019) Detection of Psychological Trauma and Suicide Risk among Emergency Medical Services Personnel: An Artificial Intelligence Approach. Biomed J Sci & Tech Res 23(3).
8. Kuo Chen Chou (2020) How the Artificial Intelligence Tool iRNA-PseU is Working in Predicting the RNA Pseudouridine Sites?. Biomed J Sci & Tech Res 24(2).
9. Philippe Funk (2023) Biomedical Computation Artificial Intelligence Challenges in Cloud Environments. Biomed J Sci & Tech Res 50(4).
10. Swati Gupta, Dheeraj Kumar Sharma, Manish Gupta K (2019) Artificial Intelligence in Diagnosis and Management of Ischemic Stroke. Biomed J Sci & Tech Res 13(3).
11. Angela Hsu, Robin Zachariah, James Han, William Karnes (2023) Artificial Intelligence for Colonoscopy: Beyond Polyp Detection – A Review of where we are Today and where AI can Take us. Biomed J Sci & Tech Res 49(3).
12. Hamid Yahya Hussain (2020) Frailty and Spousal/Partner Bereavement in Older People: A Systematic Scoping Review Protocol. Biomed J Sci & Tech Res 24(4).
13. Hergan Klaus, Zinterhof Peter, Abed Selim (2022) Challenges implementing and running an AI-Lab: Experience and Literature Review. Biomed J Sci & Tech Res 45(4).
14. Ik Whan G Kwon, Sung Ho Kim (2021) Digital Transformation in Healthcare. Biomed J Sci & Tech Res 34(5).
15. Jyoti Lamba, Taniya Malhotra, Drishti Palwankar, Vrinda Vats, Akshat Sachdeva (2023) Artificial Intelligence in Dentistry: A Literature Review. Biomed J Sci & Tech Res 51(1).
16. Jae-Eun Lee (2018) Artificial Intelligence in the Future Biobanking: Current Issues in the Biobank and Future Possibilities of Artificial Intelligence. Biomed J Sci & Tech Res 7(3).
17. Luca Marzi, Fabio Vittadello, Alessandra Andreotti, Andrea Piccin, Andrea Mega (2021) Will Artificial Intelligence Unveil Hepatocellular Carcinoma?. Biomed J Sci & Tech Res 35(4).
18. Rosario Megna, Alberto Cuocolo, Mario Petretta (2019) Applications of Machine Learning in Medicine. Biomed J Sci & Tech Res 20(5).
19. Sotiris Raptis, Christos Ilioudis, Vasiliki Softa, Kiki Theodorou (2022) Artificial Intelligence in Predicting Treatment Response in Non-Small-Cell Lung Cancer (NSCLC). Biomed J Sci & Tech Res 47(3).
20. Richard MF, Matthew RF, Andrew Mc K, Tapan K C (2018) FMTVDM©℗*** Nuclear Imaging Artificial (AI) Intelligence but First We Need to Clarify the Use Of (1) Stress, (2) Rest, (3) Redistribution and (4) Quantification. Biomed J Sci&Tech Res 7(2).
21. Omar Sayyouh (2022) Machine Learning Application to Combat Superbugs in Hospitals: A Primer to Infection Prevention Practitioners. Biomed J Sci & Tech Res 44(5).
22. Shivani S, Abhishek A, Rajvardhan A (2020) Prospects of Artificial Intelligence in Ophthalmic Practice. Biomed J Sci & Tech Res 27(5).
23. Woo Sung Son (2018) Drug Discovery Enhanced by Artificial Intelligence. Biomed J Sci & Tech Res 12(1).
24. Michael L Carty, Stephane Bilodeau (2023) Artificial Intelligence and Medical Oxygen. Biomed J Sci & Tech Res 51(2).
25. Benjamin Wu, Yucheng Liu, Meng Jou Wu, Hiram Shaish, Hong Yun Ma (2024) Usage of Artificial Intelligence in Gallbladder Segmentation to Diagnose Acute Cholecystitis. A Case Report. Biomed J Sci & Tech Res 55(2).
26. Min Wu (2019) Modeling of an Intelligent Electronic Medical Records System. Biomed J Sci & Tech Res 19(4).
27. Mingbo Zhang, Huipu Han, Zhili Xu, Ming Chu (2019) Applications of Machine Learning in Drug Discovery. Biomed J Sci & Tech Res 23(1).
28. McGee Robert W (2020) Qigong: A Bibliography of Books and Other Materials, Fayetteville State University, Broadwell College of Business and Economics, Studies in the Economics of Qigong, No. 1, August 25.
29. McGee Robert W (2020) A Bibliography of Recent Medical Research on Qigong, Fayetteville State University, Broadwell College of Business and Economics. Studies in the Economics of Qigong 2.
30. McGee Robert W (2020) Ba Duan Jin as a Treatment for Physical Ailments: A Bibliography of Recent Medical Research. Fayetteville State University, Broadwell College of Business and Economics. Studies in the Economics of Qigong 3.
31. McGee Robert W (2020) Wu Qin Xi as a Treatment for Physical Ailments: A Bibliography of Recent Medical Research. Fayetteville State University, Broadwell College of Business and Economics, Studies in the Economics of Qigong 4.
32. McGee Robert W (2020) The Use of Yi Jin Jing to Treat Illness: A Summary of Three Studies. Fayetteville State University, Broadwell College of Business and Economics, Studies in the Economics of Qigong 5.
33. McGee Robert W (2020) Qigong and the Treatment and Prevention of COVID-19. Fayetteville State University, Broadwell College of Business and Economics, Studies in the Economics of Qigong 6.
34. McGee Robert W (2020) Qigong and the Treatment and Prevention of Cancer. Fayetteville State University, Broadwell College of Business and Economics, Studies in the Economics of Qigong 7.
35. McGee Robert W (2021) Tai Chi, Qigong and Transgender Health. Fayetteville State University, Broadwell College of Business and Economics, Studies in the Economics of Tai Chi and Qigong 8.
36. McGee Robert W (2021) The Use of Yi Jin Jing to Treat Illness: A Summary of Three Studies. Academia Letters Article 547.
37. McGee Robert W (2021) Tai Chi, Qigong and the Treatment of Disease. Biomedical Journal of Scientific & Technical Research 34(2): 26627-26633.
38. McGee Robert W (2021) Tai Chi, Qigong and the Treatment of Cancer. Biomedical Journal of Scientific & Technical Research 34(5): 27,173-27,182.
39. McGee Robert W (2021) Tai Chi, Qigong and the Treatment of Depression and Anxiety. Biomedical Journal of Scientific & Technical Research 36(2): 28350-28354.
40. McGee Robert W (2021) Tai Chi, Qigong and the Treatment of Arthritis. Biomedical Journal of Scientific & Technical Research 37(5): 29724-29734.
41. McGee Robert W (2021) Tai Chi, Qigong and the Treatment of Hypertension. Biomedical Journal of Scientific & Technical Research 39(1): 31055-31062.
42. McGee, Robert W (2021) Ba Duan Jin and the Treatment of Illness in General, and Cognitive Impairment in Particular. Biomedical Journal of Scientific & Technical Research 40(2): 32058-32065.
43. McGee, Robert W (2022) Qigong and the Treatment of Illness: Recent Case Studies. Biomedical Journal of Scientific & Technical Research 43(1): 34250-35253.
44. McGee Robert W (2022) A Suggestion for Treating Amyotrophic Lateral Sclerosis (ALS). Biomedical Journal of Scientific & Technical Research 44(4): 35627-35631.
45. McGee Robert W (2022) Using Tai Chi and Qigong to Treat Cancer Symptoms. Biomedical Journal of Scientific & Technical Research 45(2): 36333-36336.
46. McGee Robert W (2022) Traditional Chinese Medicine and the Treatment of Cancer. Biomedical Journal of Scientific & Technical Research, 47(4): 38,636-38,639.
47. McGee Robert W (2023) Recent Studies in Traditional Chinese Medicine (TCM). Biomedical Journal of Scientific & Technical Research 50(4): 41817-41820.
48. McGee Robert W (2023) Some Beneficial Health Effects of Tai Chi and Qigong. Biomedical Journal of Scientific & Technical Research 52(3): 43813-43817.
49. McGee Robert W (2023) Tai Chi, Qigong and the Treatment of Dementia. Biomedical Journal of Scientific & Technical Research 53(5): 45080-45085.
50. McGee Robert W (2024) Tai Chi, Qigong and the Treatment of Breast Cancer. Biomedical Journal of Scientific & Technical Research 54(3): 46024-46027.
51. McGee Robert W (2024) Using Artificial Intelligence to Conduct Research on the Health Benefits of Tai Chi: A Pilot Study. Biomedical Journal of Scientific & Technical Research 55(2): 46838-46841.
52. McGee Robert W (2024) Tai Chi, Qigong and the Treatment of Lung Cancer: A Study in Artificial Intelligence. Biomedical Journal of Scientific & Technical Research 55(4): 47220-47225.
53. McGee Robert W (2024) Incorporating Qigong into a Western Medical Practice: A Study in Artificial Intelligence. Biomedical Journal of Scientific & Technical Research 55(5): 47401-47405.
54. McGee Robert W (2024) Incorporating Baduanjin into a Western Medical Practice: A Study in Artificial Intelligence and Traditional Chinese Medicine (TCM). Biomedical Journal of Scientific & Technical Research 56(1): 47739-47744.
55. McGee Robert W (2023) Don’t Trust ChatGPT: A Case Study of a Defective Research Tool. Working Paper 21.
56. Copilot [Copilot GPT4 Microsoft].
57. Ford CG, Vowles KE, Smith BW, Kinney AY (2020) Mindfulness and Meditative Movement Interventions for Men Living with Cancer: A Meta-analysis. Ann Behav Med 54(5): 360-373.
58. Frantzis Bruce (2010) Dragon and Tiger Medical Qigong, Volume 1. Fairfax, CA: Energy Arts.
59. Frantzis Bruce (2014) Dragon and Tiger Medical Qigong Volume 2: Qi Cultivation Principles and Exercises. North Atlantic Books.
60. Jahnke Roger (1997) The Healer Within. San Francisco: Harper.
61. Jahnke Roger (2002) The Healing Promise of Qi. New York: Contemporary Books, a division of McGraw-Hill.
62. Jingwei li, Zhu Jianping (2014) The Illustrated Handbook of Chinese Qigong Forms from the Ancient Texts. London & Philadelphia: Singing Dragon.
63. Johnson Jerry Alan (2000) Chinese Medical Qigong Therapy: A Comprehensive Clinical Guide. Pacific Grove, CA: International Institute of Medical Qigong.
64. Johnson Jerry Alan (2005) Chinese Medical Qigong Therapy, Vol. 1: Energetic Anatomy and Physiology. Pacific Grove, CA: International Institute of Medical Qigong.
65. Johnson Jerry Alan (2005) Chinese Medical Qigong Therapy, Vol. 2: Pacific Grove, CA: International Institute of Medical Qigong.
66. Johnson Jerry Alan (2002) Chinese Medical Qigong Therapy, Vol. 3: Pacific Grove, CA: International Institute of Medical Qigong.
67. Johnson Jerry Alan (2002) Chinese Medical Qigong Therapy, Vol. 4: Prescription Exercises and Meditations, Treatment of Internal Diseases, Pediatrics, Geriatrics, Gynecology, Neurology, and Energetic Psychology. Pacific Grove, CA: International Institute of Medical Qigong.
68. Johnson Jerry Alan (2005) Chinese Medical Qigong Therapy, Vol. 5: An Energetic Approach to Oncology. Pacific Grove, CA: International Institute of Medical Qigong.
69. Korahais Anthony (2022) Flowing Zen: Finding True Healing with Qigong. Kindle Scribe.
70. (2008) Chinese Health Qigong Association. Ba Duan Jin. Beijing: Foreign Languages Press.
71. (2007) Chinese Health Qigong Association. Liu Zi Jue. Beijing: Foreign Languages Press.
72. (2008) Chinese Health Qigong Association. Wu Qin Xi. Beijing: Foreign Languages Press.
73. (2014) Chinese Health Qigong Association. Da Wu. Beijing: Foreign Languages Press.
74. (2014) Chinese Health Qigong Association. Shi Er Duan Jin. Beijing: Foreign Languages Press.
75. (2014) Chinese Health Qigong Association. Daoyin Yangsheng Gong Shi Er Fa. Beijing: Foreign Languages Press.
76. Chinese Health Qigong Association. (2014). Mawanhdui Daoyin Shu. Beijing: Foreign Languages Press.
77. (2014) Chinese Health Qigong Association. Taiji Yangsheng Zhang. Beijing: Foreign Languages Press.
78. (2024) PubMed. https://pubmed.ncbi.nlm.nih.gov/.
79. Gao Y, Yu L, Li X, Yang C, Wang A (2021) The Effect of Different Traditional Chinese Exercises on Blood Lipid in Middle-Aged and Elderly Individuals: A Systematic Review and Network Meta-Analysis. Life (Basel) 11(7):714.
80. Elicit (2024). https://elicit.com/.
81. Guo Y, Xu M, Wei Z, Hu Q, Chen Y (2018) Beneficial Effects of Qigong Wuqinxi in the Improvement of Health Condition, Prevention, and Treatment of Chronic Diseases: Evidence from a Systematic Review. Evidence-based Complementary and Alternative Medicine: eCAM.
82. McGee Robert W (2020) Ba Duan Jin As a Treatment for Physical Ailments: A Bibliography of Recent Medical Research.
83. Sancier KM (1996) Medical applications of qigong. Alternative therapies in health and medicine 2(1): 40-46.
84. Chen X, Cui J, Li R, Norton R, Park J, et al. (2019) Dao Yin (a.k.a. Qigong): Origin, Development, Potential Mechanisms, and Clinical Applications. Evidence-based Complementary and Alternative Medicine: eCAM.
85. Xi W, Jing, YJ (2021) Tai Chi, Qigong and the Treatment of Disease.
86. Sancier KM (2001) Search for medical applications of qigong with the Qigong Database. Journal of alternative and complementary medicine 7(1): 93-95.
87. Li T, Yeh M (2005) The application of qi-gong therapy to health care. Hu li za zhi The journal of nursing 52(3): 65-70.
88. Chen KW, Liu T, Zhang H, Lin Z (2009) An analytical review of the Chinese literature on Qigong therapy for diabetes mellitus. The American journal of Chinese medicine 37(3): 439-57.