Evidence map›Paper›PMID 26495414›Full record

ArticleTheScientificWorldJournal2015

Syndrome Differentiation Analysis on Mars500 Data of Traditional Chinese Medicine.

Yong-Zhi Li, Guo-Zheng Li, Jian-Yi Gao, Zhi-Feng Zhang, Quan-Chun Fan, Jia-Tuo Xu, Gui-E Bai, Kai-Xian Chen, Hong-Zhi Shi, Sheng Sun and 9 more

Open access · goldAbstract read
In one paragraph

Article in TheScientificWorldJournal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Big data is essential for further development of integrative medicine.Chinese journal of integrative medicine · 2015
    Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 3 institutions in 1 country.

Yong-Zhi LiChina Astronaut Research and Training Center, Beijing 100094, China.
Guo-Zheng LiData Center of Traditional Chinese Medicine, China Academy of Chinese Medicine Science, Beijing 100700, China.
Jian-Yi GaoChina Astronaut Research and Training Center, Beijing 100094, China.
Zhi-Feng ZhangShanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Quan-Chun FanChina Astronaut Research and Training Center, Beijing 100094, China.
Jia-Tuo XuShanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Gui-E BaiChina Astronaut Research and Training Center, Beijing 100094, China.
Kai-Xian ChenShanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Hong-Zhi ShiChina Astronaut Research and Training Center, Beijing 100094, China.
Sheng SunDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, China.
Yu LiuChina Astronaut Research and Training Center, Beijing 100094, China.
Feng-Feng ShaoDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, China.
Tao MiChina Astronaut Research and Training Center, Beijing 100094, China.
Xin-Hong JiaShanghai Daosheng Medical Technology Co. Ltd., Shanghai 201203, China.
Shuang ZhaoChina Astronaut Research and Training Center, Beijing 100094, China.
Jia-Chang ChenDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, China.
Jun-Lian LiuChina Astronaut Research and Training Center, Beijing 100094, China.
Yu-Meng GuoDepartment of Control Science and Engineering, Tongji University, Shanghai 201804, China.
Li Ping TuShanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
China Astronaut Research and Training Center · CNShanghai University of Traditional Chinese Medicine · CNTongji University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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%.

Indexed as

Medicine, Chinese TraditionalSpacecraftAlgorithmsHumansModels, BiologicalSyndrome

Identifiers

PMID26495414
PMCPMC4606216
OpenAlexW2126775827

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.