Interval-Valued Cloud Model Based Personal Sub-health Status Diagnosing Prototype System on TCM Syndrome Data

According to the Traditional Chinese Medicine (TCM) theory, there are a number of TCM syndromes closely related to the sub-health status. In this paper, a personal sub-health status diagnosing prototype system, which acquires users´ answers from health-related questions list, head images and videos, to give the diagnosis about the users´ health states. The system can infer users´ syndromes named in the Diagnostics of Chinese Medicine by calculating the degree of the given syndromes. The methods utilized about data-acquisition, doctor labeling, feature extraction and data mining are introduced. In the particular, the interval-valued cloud model is conducted to infer the syndromes on the basis of TCM doctors´ diagnosis data. The experimental results are analyzed and compared.