Evidence map›Paper›PMID 32086994›Full record

ReviewJournal of evidence-based medicine2020

Brief introduction of medical database and data mining technology in big data era.

Jin Yang, Yuanjie Li, Qingqing Liu, Li Li, Aozi Feng, Tianyi Wang, Shuai Zheng, Anding Xu, Jun Lyu

Abstract readReview
In one paragraph

Review in Journal of evidence-based medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 276 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
276citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

276 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Trial
  14. Trial
  15. Trial
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

216 more citing papers are in PubMed but not listed here.

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

9 authors.

Jin YangDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Yuanjie LiDepartment of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Qingqing LiuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Li LiDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Aozi FengDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Tianyi WangSchool of Public Health, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China.
Shuai ZhengSchool of Public Health, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China.
Anding XuDepartment of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Jun LyuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.

Funding

National Social Science Foundation of China 16BGL183
6 · The paper itself

Abstract

Data mining technology can search for potentially valuable knowledge from a large amount of data, mainly divided into data preparation and data mining, and expression and analysis of results. It is a mature information processing technology and applies database technology. Database technology is a software science that researches manages, and applies databases. The data in the database are processed and analyzed by studying the underlying theory and implementation methods of the structure, storage, design, management, and application of the database. We have introduced several databases and data mining techniques to help a wide range of clinical researchers better understand and apply database technology.

Indexed as

Big DataData ManagementData MiningDatabases, FactualSoftwarebig datadatabasedata miningmethodtechnology

Identifiers

PMID32086994
PMCPMC7065247

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.