Mars500 study was a psychological and physiological isolation experiment conducted by Russia, the European Space Agency, and China, in preparation for an unspecified future manned spaceflight to the planet Mars. Its intention was to yield valuable psychological and medical data on the effects of the planned long-term deep space mission. In this paper, we present data mining methods to mine medical data collected from the crew consisting of six spaceman volunteers. The synthesis of the four diagnostic methods of TCM, inspection, listening, inquiry, and palpation, is used in our syndrome differentiation. We adopt statistics method to describe the syndrome factor regular pattern of spaceman volunteers. Hybrid optimization based multilabel (HOML) is used as feature selection method and multilabel k-nearest neighbors (ML-KNN) is applied. According to the syndrome factor statistical result, we find that qi deficiency is a base syndrome pattern throughout the entire experiment process and, at the same time, there are different associated syndromes such as liver depression, spleen deficiency, dampness stagnancy, and yin deficiency, due to differences of individual situation. With feature selection, we screen out ten key factors which are essential to syndrome differentiation in TCM. The average precision of multilabel classification model reaches 80%.
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