Bridging Traditional Wisdom and Modern Diagnostics: Optimizing Chronic Kidney Disease Management through Technological Integration of Traditional Chinese Medicine and Western Medicine
DOI:
https://doi.org/10.62051/xp77ha77Keywords:
Chronic Kidney Disease; Integrative Medicine; Traditional Chinese Medicine; Western Medicine; Modern Technology.Abstract
Chronic kidney disease (CKD) is a major and increasing issue for public health around the world and places a heavy burden on healthcare systems globally. Current western medical (WM) treatments are relatively developed but still face difficulties in stopping the advancement of the disease and addressing the complete and complicated symptomatology of the disease at later stages. Meanwhile, the use of traditional Chinese medicine (TCM) that comes with a whole-istic philosophy and rich experience over many years in treating diseases of the kidneys can work hand-in-hand with the accurate diagnoses and application therapies of WM to improve the outcomes for patients and make their quality of life better. Some among them are the rapid development of modern technologies like Artificial Intelligence (AI), big data analytics, wearable devices, and multi-omics technologies that can bridge the gap between the experiential knowledge inherent in TCM's pattern differentiation and WM's diagnostic precision, offering possibilities for realizing TCM theory as well as paving ways for making individualized and integrative treatment plans. This paper will review the existing CKD management within both WM and TCM paradigms, elaborate on how different modern technologies can foster integration in CKD diagnosis and treatment then explore the potential future prospects of this integrative model for optimizing CKD care.
Downloads
References
[1] P. Cockwell, L.A. Fisher, The global burden of chronic kidney disease, The Lancet 395 (2020) 662-664.
[2] A.S. Ferreira, A.J. Lopes, Chinese medicine pattern differentiation and its implications for clinical practice, Chinese journal of integrative medicine 17 (2011) 818-823.
[3] K.W. Chan, T.Y. Chow, K.Y. Yu, Y. Feng, L. Lao, Z. Bian, S.C.W. Tang, Effectiveness of integrative Chinese–Western medicine for chronic kidney disease and diabetes: a retrospective cohort study, The American Journal of Chinese Medicine 50 (2022) 371-388.
[4] J.Y. Ng, H. Cramer, M.S. Lee, D. Moher, Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare, Integrative Medicine Research 13 (2024) 101024.
[5] G.J. Schwartz, S.L. Furth, Glomerular filtration rate measurement and estimation in chronic kidney disease, Pediatric nephrology 22 (2007) 1839-1848.
[6] N. Grenier, E. Quaia, P.V. Prasad, L. Juillard, Radiology imaging of renal structure and function by computed tomography, magnetic resonance imaging, and ultrasound, Seminars in nuclear medicine 41 (2011) 45-60.
[7] A. Levin, P.E. Stevens, R.W. Bilous, J. Coresh, A.L. De Francisco, P.E. De Jong, C.G. Winearls, KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease, Kidney international supplements 3 (2013) 1-150.
[8] L. Alkhatib, L.A.V. Diaz, S. Varma, A. Chowdhary, P. Bapat, H. Pan, K. Kalra, Lifestyle modifications and nutritional and therapeutic interventions in delaying the progression of chronic kidney disease: a review, Cureus 15 (2023).
[9] S.I. Taylor, Z.S. Yazdi, A.L. Beitelshees, Pharmacological treatment of hyperglycemia in type 2 diabetes, J. Clin. Investig. 131 (2021).
[10] F. Locatelli, P. Pozzoni, L. Del Vecchio, Renal replacement therapy in patients with diabetes and end-stage renal disease, J. Am. Soc. Nephrol. 15 (2004) S25-S29.
[11] D. Keown, The spark in the machine: How the science of acupuncture explains the mysteries of western medicine, Singing Dragon, 2014.
[12] A. Lu, M. Jiang, C. Zhang, K. Chan, An integrative approach of linking traditional Chinese medicine pattern classification and biomedicine diagnosis, J. Ethnopharmacol. 141 (2012) 549-556.
[13] Y. Zhong, Y. Deng, Y. Chen, P.Y. Chuang, J.C. He, Therapeutic use of traditional Chinese herbal medications for chronic kidney diseases, Kidney international 84 (2013) 1108-1118.
[14] W.T. Huang, H.H. Hung, Y.W. Kao, S.C. Ou, Y.C. Lin, W.Z. Cheng, S.T. Huang, Application of neural network and cluster analyses to differentiate TCM patterns in patients with breast cancer, Frontiers in Pharmacology 11 (2020) 670.
[15] C. Zhao, G.Z. Li, C. Wang, J. Niu, Advances in patient classification for traditional Chinese medicine: a machine learning perspective, Evidence‐Based Complementary and Alternative Medicine 2015 (2015) 376716.
[16] C.C. Kuo, C.M. Chang, K.T. Liu, W.K. Lin, H.Y. Chiang, C.W. Chung, K.T. Chen, Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning, NPJ digital medicine 2 (2019) 29.
[17] M.H. Tania, K. Lwin, M.A. Hossain, Advances in automated tongue diagnosis techniques, Integrative Medicine Research 8 (2019) 42-56.
[18] E. Itelman, G. Shlomai, A. Leibowitz, S. Weinstein, M. Yakir, I. Tamir, G. Segal, Assessing the usability of a novel wearable remote patient monitoring device for the early detection of in-hospital patient deterioration: observational study, JMIR Formative Research 6 (2022) e36066.
[19] K.J. Karczewski, M.P. Snyder, Integrative omics for health and disease, Nature Reviews Genetics 19 (2018) 299-310.
[20] W. Ziyi, Z. Tingyu, W. Boyang, L. Shao, TCM network pharmacology: New perspective integrating network target with artificial intelligence and multi-modal multi-omics technologies, Chinese Journal of Natural Medicines (2024).
[21] G. Gembillo, R. Siligato, D. Santoro, Personalized medicine in kidney disease, J. Pers. Med. 13 (2023) 1501.
[22] W.C. Tsai, C.H. Kuo, C.F. Lee, Research on Augmented Reality Design of Diet for Elderly Patients with Chronic Kidney Disease, in: International Conference on Human-Computer Interaction, Springer, Cham, 2025, pp. 273-289.
[23] X. Zhou, S. Chen, B. Liu, R. Zhang, Y. Wang, P. Li, X. Yan, Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support, Artificial Intelligence in medicine 48 (2010) 139-152.
[24] N. Ali, W. Shah, Integrative Systems and Holistic Health Records: A New Paradigm in Personalized Medicine, 2025.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Transactions on Materials, Biotechnology and Life Sciences
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
