| Literature DB >> 32033545 |
Lieyu Huang1, Xuefeng Shi2,3, Nan Zhang4, Ya Gao1, Qian Bai1, Liming Liu1, Ling Zuo5, Baolin Hong1.
Abstract
BACKGROUND: Stroke is a major cause of death and disability worldwide. Over the years, traditional medicines for stroke treatment have undergone tremendous progress, but few bibliometric studies have been performed. This study explored the trends and issues relating to the application of traditional medicine in stroke research.Entities:
Keywords: Bibliometric analysis; Stroke; Traditional medicine; Trends; Web of science
Mesh:
Year: 2020 PMID: 32033545 PMCID: PMC7076850 DOI: 10.1186/s12906-020-2832-x
Source DB: PubMed Journal: BMC Complement Med Ther ISSN: 2662-7671
Fig. 1The world distribution and collaboration on the topic of TCAM for stroke. The distribution heat map was created using the Google Fusion Table and the collaboration map was created using CiteSpace VI software. Lines link the nodes on the map, representing the worldwide collaboration among institutes. The range and the color of the heat on the top-right corner indicate the number of articles at specific locations
Fig. 2The relational chart of AI and AAI from 2009 to 2018 for the top 5 countries. The dotted line AI = 1 represents the global average contribution to TCAM for stroke, and AAI = 1 the global average impact. The reference line y = x represents the balance of effort and impact of a country’s research
Fig. 3Dual-map overlay of journals related to TCAM for stroke topic. A total of four citation paths were identified. The journals of citing articles are on the left (a), and the journals of references on the right (b)
Fig. 4The river chart of the 10 journals with the highest number of articles. Each journal has its theme color and the width of lines represents the number of articles. The flow direction is from left to right, ranging from 2004 to 2018
Fig. 5Collaboration among institutes (a) and authors (b). Different nodes represent elements such as an institute or an author, and links between nodes represent relationships among collaborators. The color of nodes and lines stand for different years: the lighter the color, the closer the time. The outermost purple rounds of circles denote the centrality level. Nodes with high centrality are regarded as turning points or pivotal points in the research field
Fig. 633 keywords with strong citation bursts in articles published. The strength value reflects the frequency of citation