Bibliometric and research hotspots analysis of radiomics in recent five years

Abstract

Objective To investigate hotspots from researches on radiomics in recent five years. Methods Bibliographies from research literature of radiomics in recent five years in PubMed database were downloaded. The publication years, journals, countries of publication, the first authors and the frequency of Mesh major topics were counted by Bicomb 2.0 software. The affiliations were analyzed artificially. Mesh major topics appeared no less than two times were intercepted as high frequency ones and the high frequency Mesh major topics matrix were formed. SPSS 22.0 statistical software were applied for clustering analysis with matrix to get the topic hotspots. Results A total of 56 literatures were screened out, among which, there were 2 (3.6%,2/56), 3 (5.4%,3/56) ,4 (7.1%,4/56) ,28 (50.0%,28/56) and 19 (33.9%,19/56) literatures published in 2012, 2013, 2014, 2015, 2016, respectively. Twenty one of 56 (37.5%, 21/56) literatures published in 5 journals which were contained in 34 journals from 10 countries, were divided into core area, in terms of published articles of no less than 3. Frequency distribution were 18 (US), 6 (England), 2 (Netherland and Germany) and 1 (Switzerland, France, Spain, Ireland, Turkey, India), respectively, for 34 journals (56 literatures).Among the 56 literatures, US, Netherlands and Canadacontained 27, 10, 5, respectively. England had 2, as same as China, France and Czech Republic, and 1 in Germany, Spain, Hungary, Korea, Japan, India, respectively, in terms of first authors affiliated research institution. The number of high frequency major topics was 11 and among them 2 research hotspots (A and B) were clustered. One (A) was computer-aided diagnosis of non-small cell lung cancer, combined with methods of three-dimensional processing, another (B) was PET combined with computer-aided and image integration technology in the diagnosis of lung tumors. Conclusion Hotspots from researches on radiomics in recent five years are focused on computer-aided diagnosis of non-small cell lung cancer, combined with methods of three-dimensional processing, and PET combined with computer-aided and image integration technology in the diagnosis of lung tumors. Key words: Bibliometrics; Radiomics