2020_04_28_Webinar_TopicModeling

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


This is a companion discussion topic for the original entry at https://kni.me/w/Sd60WkxYYnpXDDvt