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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
A bibliometric analysis and visualization of medical data mining research
Yuanzhang Hu1, Zeyun Yu2, Xiaoen Cheng1
1School of Medical Information Engineering, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan.
This study uses bibliometrics and visualization to map medical data mining (MDM). Key findings reveal research trends, influential authors, and emerging topics like precision medicine for future focus.
Area of Science:
- Bibliometrics and Visualization
- Medical Data Mining
Background:
- Medical data mining (MDM) research is extensive globally.
- Limited bibliometric and visualization studies exist for MDM.
- Research topics and development trends in MDM remain unclear.
Purpose of the Study:
- To analyze citation characteristics, international cooperation, author cooperation, and geographical distribution in MDM.
- To provide a comprehensive overview of MDM through bibliometric and visualization techniques.
- To identify current hot topics and future research frontiers in MDM.
Main Methods:
- Applied bibliometric visualization software: VOSviewer 1.6.10 and CiteSpace V.
- Analyzed 1575 documents, focusing on publication types, authors, citations, countries, and institutions.
- Examined journal productivity and keyword frequency to understand research focus.
Main Results:
- The USA is the most productive country, with the US FDA as the leading institution.
- SHAN NH is the most prolific author, and Gillies's article is the most cited.
- Hot topics include drug discovery, medical imaging, and vaccine safety; frontier areas are reporting systems, precision medicine, and inflammation.
Conclusions:
- This bibliometric and visualization study offers a panoramic view of MDM.
- Findings provide references for new researchers regarding authors, journals, institutions, and countries.
- Identified emerging trends like precision medicine can guide future research directions.
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