首页|Decision of Acupoints in Acupuncture and Moxibustion Treatment by Deep Learning
Decision of Acupoints in Acupuncture and Moxibustion Treatment by Deep Learning
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NSTL
Most of the acupuncture and moxibustion treatments in Traditional Chinese Medicine are carried out based on the clinical experience of individual acupuncturists, from the examination of the patient's illness to the selection of acupoints and the decision of treatment prescriptions, due to which the same disease is often treated with different treatments. Therefore, regarding acupuncture and moxibustion treatment, it is necessary to establish objective and unified research methods and evaluation criteria based on Traditional Chinese Medicine, western medicine, and science and technology. In this paper, we propose a method to determine the acupoints of acupuncture and moxibustion treatment according to the patient's symptoms by using deep learning. Specifically, in this paper we build a database of symptoms and acupuncture and moxibustion treatment prescriptions, and perform learning by deep learning using several models. Furthermore, we evaluate the models using the test data and discuss the evaluation criteria.
Artificial intelligenceMachine learningDeep learningAcupuncture and moxibustionTraditional chinese medicine
Hang YANG、Ren WU、Mitsuru NAKATA、Qi-Wei GE
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The Graduate School of East Asian Studies, Yamaguchi Univ.
NSTL
