Investigation of Research Trends in Radiological Technology Using Text Mining

Abstract

The purpose of this study was to investigate the trends of researches regarding radiological technology. We collected research papers published from 2007 to 2017 from Japanese Society of Radiological Technology (JSRT). After preprocessing, we performed morphological analysis using terminology from Japan Radiological Society, Japan Society of Medical Physics, and JSRT to extract technical terms. Furthermore, we calculated the Jaccard similarity coefficient to represent the similarity between two terms. This value ranged from 0 to 1, where 0 implied that the terms were completely dissimilar. Finally, in order to detect terms that characteristically appear in each year, we visualized co-occurring terms by using network diagrams. From the morphological analysis, 5471 technical terms were extracted. The most frequency term was "image" from 2007 to 2017. "Phantom" and "CT" were frequent terms after "image." In addition, the number of research papers including "image," "phantom," and "CT" were increasing. For network analysis, the characteristic terms in 2007 were "filter" and "HU"; those in 2012 were "dimension," "standard deviation,"and "artifact"; and those in 2017 were "PET," "scattered ray," and "collimator." In conclusion, the highest interest research topic in radiological technology was "image," and recently, there has been a tendency to be interested in topics related to nuclear medicine.