Abstract Mining

TL;DR

This paper presents an application for clustering and exploring PubMed abstracts, enabling researchers to analyze, filter, and download grouped publication data based on user-defined clusters and keywords.

Contribution

The paper introduces a novel tool that clusters PubMed abstracts and provides interactive features for detailed exploration and filtering of biomedical literature.

Findings

Effective clustering of PubMed abstracts based on non-trivial words

User-friendly interface for exploring clusters, titles, and abstracts

Ability to exclude documents with specific keywords

Abstract

We have developed an application that will take a "MEDLINE" output from the PubMed database and allows the user to cluster all non-trivial words of the abstracts of the PubMed output. The number of clusters to use can be selected by the user. A specific cluster may be selected, and the PMIDs and dates for all publications in the selected cluster are displayed underneath. See figure 2, where cluster 12 is selected. The application also has an "Abstracts" tab, where the abstracts for the selected cluster can be perused. Here, it is also possible to download a HTML file containing the PMID, date, title, and abstract for each publication in the selected cluster. A third tab is called "Titles", where all the titles for the selected cluster are displayed. Via a "Use Cluster" button, the selected Cluster can itself be clustered. A "Back" button allows the user to return to any previous state. Finally, it is also possible to exclude documents whose abstracts contain certain words (see figure 3). The application will allow researchers to enter general search terms in the PubMed search engine, then use the application to search for publications of special interest within those search terms.