Mapping Precision Medicine Research: A Scientometric and Network Visualization Approach
DOI:
https://doi.org/10.5281/zenodo.15209312Keywords:
Precision medicine, personalized healthcare, Digital twin, Deep learning, Artificial Intelligence (AI)Abstract
In the realm of Precision medicine, it has been increasingly recognized that individuals affected by the same disease have intricate biological profiles. Precision medicine strives to enhance the health of patients by acquiring the most effective medicines based on individual variations in genes, including somatic and inherited. The field has endured rapid advancements prompted by technologies such as Big Data, Digital Twins, Artificial Intelligence, Deep Learning, and Data Analytics. This study employs quantitative approach to execute Sciento- metric Analysis of the articles indexed in the Web of Science Database. A searchingstring was generated through the selection of pertinent keywords, and certain parameters such as publishing year, research subject and financing organization were examined. The bibliometric networks were examined and visualized by employing software named VOSViewer. A total of 1352 papers were obtained between 2013 and 2022, with a notable surge in research output in 2019 and increased to 203-219 publications annually over the preceding three years. The most substantial disciplines in healthcare are genetics and healthcare science, which contributes to an upsurge in publications and citations. Genetic testing and genomic medicine are among the foremost recent trends in Precision medicine research. This paper provides the implementation, most recent trends, and worldwide study geography over the preceding ten years whichaid in determining preliminary research and providing recommendations for further studies.
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