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基于“火星-500”项目数据的中医证候分析

Syndrome Differentiation Analysis on Mars500 Data of Traditional Chinese Medicine.

作者信息

Li Yong-Zhi, Li Guo-Zheng, Gao Jian-Yi, Zhang Zhi-Feng, Fan Quan-Chun, Xu Jia-Tuo, Bai Gui-E, Chen Kai-Xian, Shi Hong-Zhi, Sun Sheng, Liu Yu, Shao Feng-Feng, Mi Tao, Jia Xin-Hong, Zhao Shuang, Chen Jia-Chang, Liu Jun-Lian, Guo Yu-Meng, Tu Li Ping

机构信息

China Astronaut Research and Training Center, Beijing 100094, China.

Data Center of Traditional Chinese Medicine, China Academy of Chinese Medicine Science, Beijing 100700, China.

出版信息

ScientificWorldJournal. 2015;2015:125736. doi: 10.1155/2015/125736. Epub 2015 Oct 1.

Abstract

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%.

摘要

“火星-500”研究是由俄罗斯、欧洲航天局和中国开展的一项心理和生理隔离实验,旨在为未来一项未明确的载人火星飞行任务做准备。其目的是获取有关计划中的长期深空任务影响的有价值的心理和医学数据。在本文中,我们提出了数据挖掘方法,用于挖掘从由六名宇航员志愿者组成的乘员组收集的医学数据。我们在辨证中运用了中医四种诊断方法,即望、闻、问、切的综合运用。我们采用统计方法来描述宇航员志愿者的证素规律模式。采用基于混合优化的多标签(HOML)作为特征选择方法,并应用多标签k近邻(ML-KNN)。根据证素统计结果,我们发现气虚是整个实验过程中的基础证型模式,同时,由于个体情况的差异,还存在肝郁、脾虚、湿滞、阴虚等不同的兼夹证型。通过特征选择,我们筛选出了对中医辨证至关重要的十个关键因素。多标签分类模型的平均精度达到80%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f5d/4606216/3c7bd4107f7f/TSWJ2015-125736.001.jpg

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