Scientometric Study of Research in Information Retrieval in Medical Sciences

Mapping scientific trends is one of the most important missions of scientometric research for effective research. The main goal of this paper was to visualize and draw the intellectual and cognitive structures of information retrieval (IR) in the medical sciences using science mapping.   

In this cross-sectional scientometric study, we recruited all documents indexed in the Web of Science database with the topic of storing and retrieval of information in medical sciences. To analyze the results, 3 software, SciMAT-v1.1.04, VOSviewer-v1.6.14, CitNetExplorer_v1.0.0, were used.   

Our results showed that most scientific productions in this field fall into 2 categories: (1) effective methods of organizing information and (2) application and operation of the IR system in the process of intelligent questioning and answering, and analyzing information behaviors of physicians and health professionals. The results showed that the similarity index increased over time from 0.43 to 0.71. Analysis of the findings showed that similarity measures, expert systems, concepts, experience, answers, and multimodel IR clusters were considered as mature and completely centralized clusters in the first quarter of the strategic chart.   

Because of the dramatic approximation of the vocabulary used by researchers and a relative slowdown in the growth rate of the subject's domain in the last decade, it seems necessary to pay attention to the expansion of the fields of IR and the application of its concepts in medical information sciences. Also, it can be recommended that designers of IR systems and techniques in medical information sciences pay more attention to human factors attentively to develop new technologies and tools.