Abstract
Traditional Chinese Medicine (TCM) for weight loss is a personalized medical treatment which is widely used and effective at present. The evaluation of TCM intervention technology for different obesity grades can provide a basis for optimizing treatment schedule. This study retrieved and selected 640 literatures about the treatment of simple obesity with Body Mass Index (BMI) information from 1980 to 2016. Through literature research, expert consultation, mathematical statistics, and machine learning, from the perspective of single intervention technology and intervention technology combination, the evaluation index system of single intervention technology based on literature and the evaluation method of intervention technology combination were established. Empirical study takes overweight patients (BMI 25–26) in obesity grade as an example. Single intervention technology evaluation found that the comprehensive top-ranking TCM intervention technology is “acupuncture, catgut embedding, electro-acupuncture and ear acupoint”. Intervention technology combination evaluation found that the most commonly used TCM intervention techniques were “electro-acupuncture and acupuncture”, “ear acupoint and acupuncture”, “ear acupoint and electro-acupuncture”, “ear acupoint, electro-acupuncture and ear acupuncture”, and “acupuncture and catgut embedding”. The conclusion was in line with clinical practice, thus confirming the rationality of the method. The establishment of this method provides a powerful reference for the clinical selection of appropriate TCM intervention technologies for obesity.
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Acknowledgements
This study was supported by the Key Scientific Research Project of Hubei Province Department of Education. (No. D20172003)
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Lin, F., Mao, S., Xie, D. (2019). Research on Evaluation Method of TCM Intervention Technology for Obesity Based on Literature. In: Wang, H., Siuly, S., Zhou, R., Martin-Sanchez, F., Zhang, Y., Huang, Z. (eds) Health Information Science. HIS 2019. Lecture Notes in Computer Science(), vol 11837. Springer, Cham. https://doi.org/10.1007/978-3-030-32962-4_26
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DOI: https://doi.org/10.1007/978-3-030-32962-4_26
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