How to cite this paper
Yaiprasert, C & Yusakul, G. (2022). Artificial intelligence for target symptoms of Thai herbal medicine by web scraping.International Journal of Data and Network Science, 6(3), 1013-1022.
Refrences
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Wang, N., Li, P., Hu, X., Yang, K., Peng, Y., Zhu, Q., Zhang, R., Gao, Z., Xu, H., Liu, B., Chen, J., & Zhou, X. (2019). Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network. Computational and Structural Biotechnology Journal, 17, 282–290.
Wen-Xiang, D., Jian-Ping, Z., Jing, L., Zhi-Ying, Y., Hua-Ying, W., Zhong- Hua, Y., Yi-Ge, Z., Wen-An, Z., & Hui-Yong, H. (2019). Research on Text Mining of Syndrome Element Syndrome Differentiation by Natural Language Processing. Digital Chinese Medicine, 2(2), 61–71.
Wolfram, S. (2017). An elementary introduction to the Wolfram langauge. Wolfram Media, Inc.
Yu, K.-H., Zhang, C., Berry, G. J., Altman, R. B., Ré, C., Rubin, D. L., & Snyder, M. (2016). Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features. Nature Communications, 7(1).
Yu, T., Li, J., Yu, Q., Tian, Y., Shun, X., Xu, L., Zhu, L., & Gao, H. (2017). Knowledge graph for TCM health preserva-tion: Design, construction, and applications. Artificial Intelligence in Medicine, 77, 48–52.
Zhou, X., Chen, S., Liu, B., Zhang, R., Wang, Y., Li, P., Guo, Y., Zhang, H., Gao, Z., & Yan, X. (2010). Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support. Artificial Intelligence in Medicine, 48(2-3), 139–152.
Cao, C., Wang, H., & Sui, Y. (2004). Knowledge modeling and acquisition of traditional Chinese herbal drugs and formu-lae from text. Artificial Intelligence in Medicine, 32(1), 3–13.
Chang, S. J., Yang, E., Lee, K.-E., & Ryu, H. (2020). Internet health information education for older adults: A pilot study. Geriatric Nursing, 42(2), 533–539.
Chen, Z., Cao, Y., He, S., & Qiao, Y. (2018). Development of models for classification of action between heat-clearing herbs and blood-activating stasis-resolving herbs based on theory of traditional Chinese medicine. Chinese Medicine, 13(1), 1–11.
Choi, E., Bahadori, M. T., Schuetz, A., Stewart, W. F. & Sun, J. (2016). Doctor AI: Predicting clinical events via recurrent neural networks. in Proceedings of Machine Learning for Healthcare, 56, 1–18.
Du, H., Yang, J., King, R. B., Yang, L., & Chi, P. (2020). COVID‐19 Increases Online Searches for Emotional and Health‐Related Terms. Applied Psychology: Health and Well-Being, 12(4), 1039–1053.
Family, A., Fashner, J., Ericson, K. & Werner, S. (2012). Treatment of the common cold in children and adults. American Family Physician, 86(2), 153–159.
Gianfredi, V., Sandro, P., & Santangelo, O. E. (2021). What can internet users’ behaviours reveal about the mental health impacts of the COVID-19 pandemic? A systematic review. Public Health, 198, 44–52.
Han, N., Qiao, S., Yuan, G., Huang, P., Liu, D., & Yue, K. (2019). A novel Chinese herbal medicine clustering algorithm via artificial bee colony optimization. Artificial Intelligence in Medicine, 101, 101760.
Jha, S., & Topol, E. J. (2016). Adapting to Artificial Intelligence. JAMA, 316(22), 2353.
Kanjanahattakij, N., Kwankhao, P., Vathesatogkit, P., Thongmung, N., Gleebbua, Y., Sritara, P., & Kitiyakara, C. (2019). Herbal or traditional medicine consumption in a Thai worker population: pattern of use and therapeutic control in chronic diseases. BMC Complementary and Alternative Medicine, 19(1), 1–9.
Kee, J. L., Hayes, E. R., & Mccuistion, L. E. (2015) Pharmacology: A patient-centered nursing process approach. Else-vier.
M, H., & Sagar, Dr. B. M. (2019). Smart Health Care Implementation Using Naïve Bayes Algorithm. International Jour-nal of Innovative Research in Computer Science & Technology, 7(3), 90–93.
MedThai, (2021). Med pedia. Medthai.
Mikkelsen, G., & Aasly, J. (2002). Manual semantic tagging to improve access to information in narrative electronic med-ical records. International Journal of Medical Informatics, 65(1), 17–29.
Murdoch, T. B., & Detsky, A. S. (2013). The Inevitable Application of Big Data to Health Care. JAMA, 309(13), 1351.
Ryan, P., Luz, S., Albert, P., Vogel, C., Normand, C., & Elwyn, G. (2019). Using artificial intelligence to assess clinicians’ communication skills. BMJ, 364, l161.
Serçekuş, P., Değirmenciler, B., & Özkan, S. (2021). Internet use by pregnant women seeking childbirth information. Journal of Gynecology Obstetrics and Human Reproduction, 50(8), 102144.
Sheikhalishahi, S., Miotto, R., Dudley, J. T., Lavelli, A., Rinaldi, F., & Osmani, V. (2019). Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review. JMIR Medical Informatics, 7(2), e12239.
Sun, X., & Qian, H. (2016). Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network. PLOS ONE, 11(6), e0156327.
Wang, N., Li, P., Hu, X., Yang, K., Peng, Y., Zhu, Q., Zhang, R., Gao, Z., Xu, H., Liu, B., Chen, J., & Zhou, X. (2019). Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network. Computational and Structural Biotechnology Journal, 17, 282–290.
Wen-Xiang, D., Jian-Ping, Z., Jing, L., Zhi-Ying, Y., Hua-Ying, W., Zhong- Hua, Y., Yi-Ge, Z., Wen-An, Z., & Hui-Yong, H. (2019). Research on Text Mining of Syndrome Element Syndrome Differentiation by Natural Language Processing. Digital Chinese Medicine, 2(2), 61–71.
Wolfram, S. (2017). An elementary introduction to the Wolfram langauge. Wolfram Media, Inc.
Yu, K.-H., Zhang, C., Berry, G. J., Altman, R. B., Ré, C., Rubin, D. L., & Snyder, M. (2016). Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features. Nature Communications, 7(1).
Yu, T., Li, J., Yu, Q., Tian, Y., Shun, X., Xu, L., Zhu, L., & Gao, H. (2017). Knowledge graph for TCM health preserva-tion: Design, construction, and applications. Artificial Intelligence in Medicine, 77, 48–52.
Zhou, X., Chen, S., Liu, B., Zhang, R., Wang, Y., Li, P., Guo, Y., Zhang, H., Gao, Z., & Yan, X. (2010). Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support. Artificial Intelligence in Medicine, 48(2-3), 139–152.