Literature Clustering Analysis of Geriatric Nursing Research
- DOI
- 10.2991/icoi-19.2019.136How to use a DOI?
- Keywords
- Geriatrics Nursing, PubMed, Clustering Analysis
- Abstract
The purpose of our work is to obtain a multi-dimensional research hotspot after literature cluster analysis of global gerontology research hotspots from 2008 to 2017. Clustering information, such as major research institutions, journals, related diseases, treatment methods, chemical drugs and Chinese herbal medicine, cross-subjects was extracted using “geriatrics nursing” as a search subject based on the PubMedplus retrieval and clustering analysis system. The analysis showed that there are 10 major diseases related to gerontological nursing, such as neurological diseases, Alzheimer's disease, central nervous system diseases, brain diseases, dementia, etc.; the main chemicals associated with gerontology are indigo carmine, amaranth Nearly 20 species such as dye, 30 kinds of Chinese herbal medicines such as tea tree root, and clusters of subjects related to geriatric nursing include geriatrics, rehabilitation medicine, psychosis and mental health. PubMedplus is a very useful biomedical text mining tool. The cluster analysis of the research focus of geriatric nursing can grasp the overall development trend of geriatric nursing at home and abroad, reveal the frontier research hotspots, and provide valuable clues for basic and clinical research.
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Kaijun Yu AU - Ruiyi Gong AU - Minyan He AU - Shanshan Hu AU - Rui Wang PY - 2019/10 DA - 2019/10 TI - Literature Clustering Analysis of Geriatric Nursing Research BT - Proceedings of the 2019 International Conference on Organizational Innovation (ICOI 2019) PB - Atlantis Press SP - 774 EP - 778 SN - 2352-5428 UR - https://doi.org/10.2991/icoi-19.2019.136 DO - 10.2991/icoi-19.2019.136 ID - Yu2019/10 ER -