This workflow shows a topic modeling approach using documents related to user-selected diseases of interest. It starts, after selecting disease names, with the extraction of text documents from the database PubMed and performs topic modeling using the Latent Dirichlet Allocation (LDA) method. Additionally, two interactive views will created using components. Data sources used in this workflow: - Disease list: randomly selected diseases from OMIM (Online Mendelian Inheritance in Man) - Scientific literature: PubMed
Used extensions & nodes
Created with KNIME Analytics Platform version 4.1.2
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