GridaMed: A Tool for Pubmed Search and Research Trend Map Generation

• Published in: 2018 Portland International Conference on Management of Engineering and Technology (PICMET) pp. 1 - 3
• Main Authors: Yang, Heyoung, Lee, Hyuck Jai, Hong, Sung Wha
• Format: Conference Proceeding
• Language: English
• Published: Portland International Conference on Management of Engineering and Technology, Inc. (PICMET) 01-08-2018
• Subjects: Correlation; Feature extraction; Google; Mesh networks; Visualization
• DOI: 10.23919/PICMET.2018.8481956

PubMed is the most frequently used search tool for the professionals in biomedical domain. Many auxiliary tools to PubMed have been proposed to help the users with searching and acquiring knowledge from electronic literatures. However, they are insufficient to overcome the challenge from drastic increase in the size of the literature, which triggered the need for a new tool. The authors introduce a new tool, GridaMed, to visualize the recent research trend based on the retrieved documents corresponding to a user's simple search query to PubMed. GridaMed utilizes the Medical Subject Headings (MeSH) tagged in the PubMed documents, which are extracted from the documents, and generates the MeSH map (or MeSH network) by calculating the correlations of every MeSH term pairs based on the similarities of the keywords from the document titles. GridaMed provides a feature called 'click-and-link', which provides the list of documents containing a specific MeSH represented as a node in the MeSH map. The MeSH map can be used as a 'guide map for travelers' for an easy acquisition of the knowledge on the research trend. The combination of PubMed and MeSH map is expected to be an effective complementary system for biomedical professionals who find it difficult to search and analyze information due to the explosive increase in the literature.