Abstract
Alzheimer’s disease is a major disease that endangers people’s health. Its occurrence and development involve complex biological systems in the human body. Traditional Chinese medicine pays attention to comprehensive regulation and control, which is in line with complex biological systems. With thousands of years of history, some classic pharmaceutical formulas and prescriptions have been formed. Through in-depth mining of Chinese medicine data for treating Alzheimer’s disease, we extract the drug attributes of traditional Chinese medicine prescriptions for treating Alzheimer’s disease, and using machine learning methods and deep learning methods to model and analyze the properties of medicines, at the same time mining effective drug attributes. The model can also predict the effectiveness of new Chinese medicine prescriptions for treating Alzheimer’s disease. In this paper, different machine learning algorithms are used to model the drug properties in traditional Chinese medicine prescriptions. The highest accuracy of the model can reach more than 62%. The experimental results show that the method proposed has certain research value and prospect in the study of traditional Chinese medicine.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Li, L., Zhang, L.: Action characteristics of traditional chinese medicine in treatment of Alzheimer’s disease. Prog. Biochemistry and Biophys, 039(8), 816–828 (2013)
Sun, Z.-K., Yang, H.-Q., Chen, S.-D.: Traditional Chinese medicine: a promising candidate for the treatment of Alzheimer’s disease. Translational Neurodegeneration 2(1), 6 (2013)
Gao, J.J., Inagaki, Y., Li, X., Kokudo, N., Tang, W.: Research progress on natural products from traditional Chinese medicine in treatment of Alzheimer’s disease. Intractable Rare Dis Res 7(2), 46–57 (2013)
Ping, L., Kong, M., Yuan, S., Liu, J., Wang, P.: History and experience: a survey of traditional chinese medicine treatment for Alzheimer’s disease. Evidence-Based Complementary and Alternative Med. 2014, 1–5 (2016)
Lin, H.Q., Ho, M.T., Lau, L.S., Wong, K.K., Shaw, P.C., Wan, D.C.C.: Anti-acetylcholinesterase activities of traditional Chinese medicine for treating Alzheimer’s disease. Chemico-Biol. Interact. 175(1), 352–354 (2008)
Jiang, H., Luo, X., Bai, D.: Progress in clinical, pharmacological, chemical and structural biological studies of huperzine A: a drug of traditional chinese medicine origin for the treatment of Alzheimer’s disease. Current Med. Chem. 10(21), 2231–2252 (2003)
Andong, J., et al.: Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score, Jama Neurology
Spathis, D., Vlamos, P.: Diagnosing asthma and chronic obstructive pulmonary disease with machine learning. Health Inform. J. 1204, 146045821772316 (2016)
Vijayan, V.V., Anjali, C.: Prediction and diagnosis of diabetes mellitus — A machine learning approach (2016)
Christian, S., Antonio, C., Petronilla, B., Aldo, G. M.C.Q., Isabella, C.: Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer’s disease: a machine learning approach. Front. Neurosci. 9, 625–631 (2017)
Joshi, S., et al.: Classification of Alzheimer’s Disease and Parkinson’s Disease by Using Machine Learning and Neural Network Methods (2010)
Pang, X.C., Wang, Z., Fang, J.S., Lian, W.W., Du, H.: Network pharmacology study of effective constituents of traditional Chinese medicine for Alzheimer’s disease treatment. Yao xue xue bao = Acta pharmaceutica Sinica, 51(5), 725–731 (2016)
Chen, H.-Y., et al.: Deep learning and random forest approach for finding optimal TCM formula for treatment of Alzheimer’s disease. J. Chem. Inf. Model. 59, 4 (2019)
Acknowledgements
This work was supported by the National Key Research and Development Program of China under Grand 2017YFB0802704 and National Natural Science Foundation of China under Grand 61972249.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Lu, J., Tang, P., Qiu, W., Wang, H., Guo, J. (2020). Effectiveness Analysis of Traditional Chinese Medicine for Anti-Alzheimer’s Disease Based on Machine Learning. In: Xiang, Y., Liu, Z., Li, J. (eds) Security and Privacy in Social Networks and Big Data. SocialSec 2020. Communications in Computer and Information Science, vol 1298. Springer, Singapore. https://doi.org/10.1007/978-981-15-9031-3_18
Download citation
DOI: https://doi.org/10.1007/978-981-15-9031-3_18
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9030-6
Online ISBN: 978-981-15-9031-3
eBook Packages: Computer ScienceComputer Science (R0)