Background: Medical informatics (MI) is a multidisciplinary field in which researchers pursue scientific exploration, problem-solving, and decision-making to facilitate the effective use of biomedical data, information and knowledge for the improvement of human health. The purpose of this study is to identify research fronts in the field of MI and ultimately elucidate research activities and trends in this field.
Methods: This study used topic model to identify research topics in the field of MI based on the latent Dirichlet allocation method (LDA). And the topic cloud is utilized to visualize the research topics. For identifying the research front topics, we proposed the indicators of identifying research front topics. In addition, we investigated how front topics change over time, and divided them into five categories based on the life cycle theory.
Results: The data were collected from 35981 published journal abstracts between 2007 and 2016. In the topic distribution of MI, we found that the scope of MI related research has become increasingly interdisciplinary, particular for medical data analysis. Also, in the analysis of research fronts of MI, we found that the use of natural language processing and medical text knowledge extraction play an essential role for systematic analysis and indexing of the underlying semantic contents.
Conclusions: By categorizing the research fronts, the results shows that there are twelve growing, five stable and two declining research fronts. We hope that this work will facilitate greater exploration of the method of identifying the research fronts. Moreover, the findings of this study provide an insight on the research fronts and trends in MI.