Visualization of Literature Information on Postmortem Interval Estimation Indexed by CNKI Database from 1990 to 2020.
10.12116/j.issn.1004-5619.2020.400902
- Author:
Ling-Xiao LIN
1
;
Guo-Bin XIN
2
;
Jiang-Wei KONG
1
;
Chuang-Yan ZHAI
1
Author Information
1. School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China.
2. Key Laboratory of Forensic Toxicology, Ministry of Public Security, People's Republic of China, Beijing 100192, China.
- Publication Type:Journal Article
- Keywords:
China National Knowledge Infrastructure;
CiteSpace;
bibliometrics;
forensic pathology;
postmortem interval estimation;
visualization analysis
- MeSH:
Artificial Intelligence;
Autopsy;
China;
Forensic Sciences;
Software
- From:
Journal of Forensic Medicine
2022;38(5):584-588
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:To explore the development process of the postmortem interval (PMI) research in China from January 1990 to August 2020, research hotspots in different periods, authors and cooperation between institutions, and to provide a reference for the better development of PMI inference research through the visualization of the literature information of the PMI estimation research indexed in China National Knowledge Infrastructure (CNKI).
METHODS:The information visualization analysis software CiteSpace 5.7.R1 was used to carry out big data analysis on hotspots, high-frequency keywords, authors, institutions and other information in the research literature on PMI inference from January 1990 to August 2020 indexed in CNKI.
RESULTS:The peak time of publication of PMI was from 2006 to 2010 with 114 articles. In keyword co-occurrence network, the effective hot words were forensic entomology, DNA content analysis and some emerging words such as artificial intelligence and big data. In the cooperation network of institutions, the high-frequency institutions were mainly the scientific research institutions. The author cooperation network showed a trend of co-aggregation and multi-cooperation.
CONCLUSIONS:With the development of science and technology, the research on PMI estimation based on traditional methods is mature and novel strategies are emerging. Big data and artificial intelligence combined with forensic science provide new research directions on PMI estimation.
