The Development History and Research Tendency of Medical Informatics: Topic Evolution Analysis

Abstract

Background Medical informatics has attracted the attention of researchers worldwide. It is necessary to understand the development of its research hot spots as well as directions for future research. Objective The aim of this study is to explore the evolution of medical informatics research topics by analyzing research articles published between 1964 and 2020. Methods A total of 56,466 publications were collected from 27 representative medical informatics journals indexed by the Web of Science Core Collection. We identified the research stages based on the literature growth curve, extracted research topics using the latent Dirichlet allocation model, and analyzed topic evolution patterns by calculating the cosine similarity between topics from the adjacent stages. Results The following three research stages were identified: early birth, early development, and rapid development. Medical informatics has entered the fast development stage, with literature growing exponentially. Research topics in medical informatics can be classified into the following two categories: data-centered studies and people-centered studies. Medical data analysis has been a research hot spot across all 3 stages, and the integration of emerging technologies into data analysis might be a future hot spot. Researchers have focused more on user needs in the last 2 stages. Another potential hot spot might be how to meet user needs and improve the usability of health tools. Conclusions Our study provides a comprehensive understanding of research hot spots in medical informatics, as well as evolution patterns among them, which was helpful for researchers to grasp research trends and design their studies.

Exploring the topic structure and evolutionary trends of health informatics research in library and information science

“…On the other hand, some studies use bibliometric methods to describe health informatics research through quantitative research methods such as statistical analysis (Binkheder et al , 2021; Han et al , 2022; Liu et al , 2019), social network analysis (Saheb and Saheb, 2019) and scientific knowledge mapping (Zou and Sun, 2020; Kokol et al , 2018; He et al , 2022; Liang, 2010). These studies point out that health informatics research focused on topics such as the application of computer science in health care, the impact of health informatics on patient safety and quality of care, implementation and evaluation of electronic health records and decision support systems (Saheb and Saheb, 2019; He et al , 2022), and future research trends may be patient-generated health data, deep learning algorithms, quantitative self and self-tracking tools and IoT-based decision support systems (Liu et al , 2019), and how to meet user needs and improve the usability of health tools is also a potential research hotspot (Han et al , 2022). Besides, there are also studies that have made efforts to reveal the current state of research in related areas or subfields of health informatics, such as in the areas of COVID-19 (Chen et al , 2021) and big data research in health informatics (Gu et al , 2017).…”

“…Health informatics research continues to evolve in response to advances in information technology, interest in it is increasing in both academic and applied communities, and some studies have examined the current state of health informatics research (Masic, 2013; Deng et al , 2018; Zou and Sun, 2020; Kokol et al , 2018; Han et al , 2022; He et al , 2022). Nevertheless, there are still four problems.…”

Transforming Ontology Web Language Elements into Common Terminology Service 2 Terminology Resources

“…This choice was made by the authors in order, on the one hand, to be able to use all of the features of ontologies encoded rigorously in OWL and, on the other hand, to be able to manage their temporal evolution through the standardized tools provided by CTS2. The need to follow the temporal evolution of said ontologies is obvious when considering ontologies defined in medical fields for which updating is rather frequent [10][11][12].…”