Topic mining and analysis of post-stroke cognitive impairment management based on LDA model
10.3760/cma.j.cn115682-20220208-00579
- VernacularTitle:基于LDA模型的卒中后认知障碍管理相关研究的主题挖掘与分析
- Author:
Nannan HU
1
;
Yibo WANG
;
Hongmei DUAN
;
Hong GUO
Author Information
1. 北京中医药大学护理学院，北京 102488
- Keywords:
Stroke;
Cognitive dysfunction;
LDA model;
Topic mining
- From:
Chinese Journal of Modern Nursing
2023;29(1):25-30
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the research status and hotspots of post-stroke cognitive impairment management, so as to provide basis for post-stroke cognitive impairment management.Methods:The articles on the post-stroke cognitive impairment management in the Web of Science from November 1, 2011 to November 1, 2021 were retrieved systematically. The bibliometric analysis was carried out from the aspects of year, journal and country. The Latent Dirichlet Allocation (LDA) topic model was used to mine potential topics and determine topic keywords.Results:A total of 1 815 articles were included. The overall number of the article showed a steady growth trend, with a total of 394 source publications, and the journal with the largest number of articles was Stroke (61 articles) . The United States was the main country for research in this field, with 34.93% (634/1 815) of the articles issued. Six topics were identified through the LDA topic model, including functional impairment and mental health in various fields of patients with post-stroke cognitive impairment, neuropsychological screening and evaluation tools, rehabilitation training and effect evaluation, support and health promotion of family caregivers, epidemiological characteristics and risk factors of post-stroke cognitive impairment. Conclusions:The research on the post-stroke cognitive impairment management is generally on the rise. The topic mining and analysis of the research is conducive to further providing the development direction and information support for the post-stroke cognitive impairment management.
