Machine Learning Research Trends in Traditional Chinese Medicine: A Bibliometric Review

Overview

Journal Int J Gen Med

Publisher Dove Medical Press

Specialty General Medicine

Date 2024 Nov 26

PMID 39588057

Authors

Jiekee Lim

Jieyun Li

Mi Zhou

Xinang Xiao

Zhaoxia Xu

Affiliations

Soon will be listed here.

Abstract

Background: Integrating Traditional Chinese Medicine (TCM) knowledge with modern technology, especially machine learning (ML), has shown immense potential in enhancing TCM diagnostics and treatment. This study aims to systematically review and analyze the trends and developments in ML applications in TCM through a bibliometric analysis.

Methods: Data for this study were sourced from the Web of Science Core Collection. Data were analyzed and visualized using Microsoft Office Excel, Bibliometrix, and VOSviewer.

Results: 474 documents were identified. The analysis revealed a significant increase in research output from 2000 to 2023, with China leading in both the number of publications and research impact. Key research institutions include the Shanghai University of Traditional Chinese Medicine and the China Academy of Chinese Medical Sciences. Major research hotspots identified include ML applications in TCM diagnosis, network pharmacology, and tongue diagnosis. Additionally, chemometrics with ML are highlighted for their roles in quality control and authentication of TCM products.

Conclusion: This study provides a comprehensive overview of ML applications' development trends and research landscape in TCM. The integration of ML has led to significant advancements in TCM diagnostics, personalized medicine, and quality control, paving the way for the modernization and internationalization of TCM practices. Future research should focus on improving model interpretability, fostering international collaborations, and standardized reporting protocols.

Citing Articles

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Liu S, Li X, Jiang S, Liu D, Wang J Int J Gen Med. 2025; 18:771-786.

PMID: 39967766 PMC: 11834669. DOI: 10.2147/IJGM.S502086.

References

Han Y, Zhou M, Wang L, Ying X, Peng J, Jiang M . Comparative evaluation of different cultivars of Flos Chrysanthemi by an anti-inflammatory-based NF-κB reporter gene assay coupled to UPLC-Q/TOF MS with PCA and ANN. J Ethnopharmacol. 2015; 174:387-95. DOI: 10.1016/j.jep.2015.08.044. View

Ellegaard O, Wallin J . The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics. 2015; 105(3):1809-1831. PMC: 4643120. DOI: 10.1007/s11192-015-1645-z. View

van Eck N, Waltman L . Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010; 84(2):523-538. PMC: 2883932. DOI: 10.1007/s11192-009-0146-3. View

Liu Z, He H, Yan S, Wang Y, Yang T, Li G . End-to-End Models to Imitate Traditional Chinese Medicine Syndrome Differentiation in Lung Cancer Diagnosis: Model Development and Validation. JMIR Med Inform. 2020; 8(6):e17821. PMC: 7327597. DOI: 10.2196/17821. View

Tian S, Wang J, Li Y, Xu X, Hou T . Drug-likeness analysis of traditional Chinese medicines: prediction of drug-likeness using machine learning approaches. Mol Pharm. 2012; 9(10):2875-86. DOI: 10.1021/mp300198d. View

Tang Y, Li Z, Yang D, Fang Y, Gao S, Liang S . Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning. Chin Med. 2021; 16(1):2. PMC: 7789502. DOI: 10.1186/s13020-020-00409-8. View

Ung C, Li H, Cao Z, Li Y, Chen Y . Are herb-pairs of traditional Chinese medicine distinguishable from others? Pattern analysis and artificial intelligence classification study of traditionally defined herbal properties. J Ethnopharmacol. 2007; 111(2):371-7. DOI: 10.1016/j.jep.2006.11.037. View

Huang N, Huang W, Wu J, Long S, Luo Y, Huang J . Possible opportunities and challenges for traditional Chinese medicine research in 2035. Front Pharmacol. 2024; 15:1426300. PMC: 11224461. DOI: 10.3389/fphar.2024.1426300. View

Shen Y, Zhang B, Pang X, Yang R, Chen M, Zhao J . Network Pharmacology-Based Analysis of Xiao-Xu-Ming Decoction on the Treatment of Alzheimer's Disease. Front Pharmacol. 2021; 11:595254. PMC: 7774966. DOI: 10.3389/fphar.2020.595254. View

10.

Chen H, He Y . Machine Learning Approaches in Traditional Chinese Medicine: A Systematic Review. Am J Chin Med. 2021; 50(1):91-131. DOI: 10.1142/S0192415X22500045. View

11.

Shi Y, Guo D, Chun Y, Liu J, Liu L, Tu L . A lung cancer risk warning model based on tongue images. Front Physiol. 2023; 14:1154294. PMC: 10267397. DOI: 10.3389/fphys.2023.1154294. View

12.

Wang Y, Shi X, Li L, Efferth T, Shang D . The Impact of Artificial Intelligence on Traditional Chinese Medicine. Am J Chin Med. 2021; 49(6):1297-1314. DOI: 10.1142/S0192415X21500622. View

13.

Xu Q, Zeng Y, Tang W, Peng W, Xia T, Li Z . Multi-Task Joint Learning Model for Segmenting and Classifying Tongue Images Using a Deep Neural Network. IEEE J Biomed Health Inform. 2020; 24(9):2481-2489. DOI: 10.1109/JBHI.2020.2986376. View

14.

Ding L, Zhang X, Wu D, Liu M . Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer. J Integr Med. 2021; 19(5):395-407. DOI: 10.1016/j.joim.2021.08.001. View

15.

Zhou X, Peng Y, Liu B . Text mining for traditional Chinese medical knowledge discovery: a survey. J Biomed Inform. 2010; 43(4):650-60. DOI: 10.1016/j.jbi.2010.01.002. View

16.

Lai Y, Ni Y, Kokot S . Classification of raw and roasted Semen Cassiae samples with the use of Fourier transform infrared fingerprints and least squares support vector machines. Appl Spectrosc. 2010; 64(6):649-56. DOI: 10.1366/000370210791414362. View

17.

Wang X, Liu J, Wu C, Liu J, Li Q, Chen Y . Artificial intelligence in tongue diagnosis: Using deep convolutional neural network for recognizing unhealthy tongue with tooth-mark. Comput Struct Biotechnol J. 2020; 18:973-980. PMC: 7186367. DOI: 10.1016/j.csbj.2020.04.002. View

18.

Zhang N, Yuan S, Chen T, Wang Y . Latent tree models and diagnosis in traditional Chinese medicine. Artif Intell Med. 2007; 42(3):229-45. DOI: 10.1016/j.artmed.2007.10.004. View

19.

Tian R, Xie P, Liu H . Evaluation of traditional Chinese herbal medicine: Chaihu (Bupleuri Radix) by both high-performance liquid chromatographic and high-performance thin-layer chromatographic fingerprint and chemometric analysis. J Chromatogr A. 2008; 1216(11):2150-5. DOI: 10.1016/j.chroma.2008.10.127. View

20.

Tian D, Chen W, Xu D, Xu L, Xu G, Guo Y . A review of traditional Chinese medicine diagnosis using machine learning: Inspection, auscultation-olfaction, inquiry, and palpation. Comput Biol Med. 2024; 170:108074. DOI: 10.1016/j.compbiomed.2024.108074. View